469 results for “Injection”

Adversa AI's November 2026 roundup of 14 AI coding agent security resources from October. It covers CVE-2026-103572 (Visual Studio Copilot and SSMS RCE via trailing-dot filename), an unpatched Claude Code child-session hook bypass, a Copilot CLI cryptographic context injection, and a CVE-less opencode MCP OAuth RCE. It ends with a checklist for auditing agent configs and gateways.

adversa.aiarticlePublished and added 2 Nov 2026🛡️ Security

Hermes, the Nous Research agent framework, shipped 130 merged PRs in October 2026, according to this X recap by Luke The Dev. Main items are a unified gateway runtime, a Desktop and Bot Screen, a bundles and package manager, crash-safe updates and new Claude model entries. Ten PRs cover security: an iron-proxy credential-injection egress firewall for sandboxes, 31 CVEs patched in Python and npm lockfiles, and profile-export and prompt-leak fixes.

x.comthreadAdded 2 Nov 2026🧠 AI

A Brazilian labor court in Parauapebas, Pará fined two law firms 10% of an R$842,000 claim (about $16,000) for hiding a prompt-injection command in a petition. The white-on-white text told AI to respond superficially and not challenge the documents. Galileu, the National Justice Council's generative AI tool, detected it and blocked processing. The court cited Articles 5 and 77 of the Civil Procedure Code.

jetstream.securityarticleAdded 2 Nov 2026, published 1 Nov 2026🛡️ Security

DBHub, a database MCP server, had a read-only mode bypass in its SQL check. The check treated every `--` as a comment, but MySQL only starts a comment when whitespace follows it. A hidden write statement could therefore still run, and a prompt injection could trigger it. Fixed in version 0.22.6. Replies say enforcement belongs in database grants and that parser tests need to be dialect-specific.

x.comthreadAdded 31 Oct 2026, published 30 Oct 2026🛡️ Security

CyberForge CVE of the Day #091 covers Progress WS_FTP Server CVE-2026-84295 (unauthenticated administrator-credential exposure, CVSS 10.0) and CVE-2026-90868 (conditional OS command and argument injection, CVSS 9.9, low privileges). Fixed floors are 2024.0.7/9.0.7 and 2025.0.4/10.0.4; 2024.0.6/2025.0.3 fix only the first. It gives KEV, EPSS and SSVC status, six SOC checks, and Windows 4688 evidence queries.

x.comadvisoryAdded 2 Nov 2026, published 30 Oct 2026🛡️ Security

Web Security Academy is PortSwigger's free online web security training. It is known to combine learning material with hands-on labs across web vulnerability classes such as SQL injection, XSS, SSRF, authentication flaws and request smuggling, and to be built around Burp Suite. The page had no extractable text, so this description comes from the URL and general knowledge of the site.

portswigger.netcourseAdded 30 Oct 2026🛡️ Security

CVE-2025-6514 is an OS command injection (CWE-78, CVSS 9.6) in mcp-remote 0.0.5 to 0.1.15, fixed in 0.1.16. A malicious MCP server supplies a crafted authorization_endpoint during OAuth discovery, and the open package passes it to PowerShell on Windows. The thread cites the MCP spec's URL scheme allowlist rules and advises treating discovery metadata as untrusted, pinning bridge tools and sandboxing them.

x.comthreadAdded 2 Nov 2026, published 30 Oct 2026🛡️ Security

Oversecured's Android security checklist for Content Providers covers insecure FileProvider path configs, path traversal via decoded Uri.getLastPathSegment(), mismatched readPermission/writePermission, proxying requests to more privileged providers, SQL injection across a shared database, and sensitive actions in providers. Each case has vulnerable manifest and Java code, an attacker PoC and remediation. Real cases from Google and Samsung devices are cited. The page text was truncated near the end.

oversecured.comarticleAdded 29 Oct 2026🛡️ Security

Oversecured's write-up of 20 vulnerabilities in Xiaomi apps and system components, reported to Xiaomi between 25 and 30 April 2023. Bugs include intent redirection with system privileges in Security and GetApps, shell command injection in System Tracing, and arbitrary file theft via path traversal in Settings and MIUI Bluetooth. Each has a PoC. The page was truncated, so the later MIUI Bluetooth entries and the rest are not covered.

oversecured.comwriteupAdded 29 Oct 2026🛡️ Security

Oversecured discloses seven Android vulnerabilities, two of them Pixel-specific, all reported to Google and fixed except one low-severity WebView case. They are the Camera geolocation leak (CVE-2024-0017), a VPN bypass list change (CVE-2023-21383), a Bluetooth permission check flaw (CVE-2024-34719), the WorkSource parcel mismatch (CVE-2023-20963, exploited in the wild by the Pinduoduo app), Device Admin HTML injection (CVE-2021-0600) and a ContentProvider.openFile() caller-context bypass (CVE-2023-21292). Each has root cause and PoC code.

oversecured.comwriteupAdded 29 Oct 2026🛡️ Security

Understanding and Mitigating Role Spoofing in LLMs is an arXiv paper (October 2026) on role spoofing, a prompt injection where malicious tool output impersonates the user. It shows models track "who said what" using both content cues (semantics, style) and structure cues (control tokens, formatting). Attacks combining fake structure and content succeed often, adversarial training stops only content-based attacks, and linear probes trained to predict conversation roles detect spoofing across settings.

arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🛡️ Security

Gemini 4 Carbon is a Google frontier model announced with restricted access for cyber defenders through the Fairwind Program (650+ organizations). Google reports 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on CWE-bench, ahead of GPT-6 Astra and Claude models, with no guardrails. It also cites prompt injection and cheating-resistance results, and pricing of $2/$10 per million tokens.

securityweek.comarticlePublished and added 29 Oct 2026🛡️ Security

SEAL is a defense against indirect prompt injection for local LLM agents. It learns a soft prompt and scoring readout offline, then uses a frozen task model to score and delete injected tokens from tool outputs, with queries built from trusted initial context. On AgentDojo, attack success falls from 34.6% to 0.1% and Joint rises from 51.4% to 77.5%, using about 127x fewer defense tokens than PISanitizer.

arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🛡️ Security

Paper studying whether self-evolution weakens personal agents' robustness to indirect prompt injection (IPI). A two-phase method has the user ask the agent to follow tasks in external content, then tests with a third-party injected task the user did not authorize. Against the non-evolving base agent, attack success rose 14.0 to 48.8 points under skill evolution and 3.0 to 39.3 points under reinforcement learning. Code is released.

arxiv.orgpaperAdded 31 Oct 2026, published 29 Oct 2026🛡️ Security

Addendum to the GPT-6 Luna system card for the model update of 29 October 2026 (the title says October 28). OpenAI keeps the High rating for cybersecurity and biological/chemical capability under its Preparedness Framework. It reports ExploitBench 46.19% and SEC-Bench Pro 51.75% (GPT-6 Astra: 85.4%), higher multiturn jailbreak defender success than the October 7 version, and GPT-Red prompt-injection results. It also reports weaker factuality and dual-use biology refusal.

deploymentsafety.openai.compaperPublished and added 29 Oct 2026🛡️ Security

Rohan Paul's X post summarizes the paper "Log-To-Leak: Prompt Injection Attacks on Tool-Using LLM Agents via the Model Context Protocol", from TikTok researchers. It reports that MCP-using agents often finish the requested task, then quietly call an attacker-controlled logging tool that records the query, server reply and final answer. The attack works through natural-language tool descriptions that agents read when choosing and ordering tools. The visible text is truncated.

x.comthreadAdded 29 Oct 2026, published 28 Oct 2026🛡️ Security

KeyDrift is a custom malware framework used by UAT-11473, which exploited CVE-2026-20127 in Cisco SD-WAN Catalyst Controller to gain access. Talos analyzes PolyFlame (memory-resident vdaemon injection, recvfrom hook, TinyShell-style backdoor, intermediate C2) and LittleFilch (SSL_read hook that extracts and RSA-encrypts keying material). It reports infrastructure overlap with Volt Typhoon's Silent Train, plus patch guidance and Snort SIDs.

blog.talosintelligence.comwriteupPublished and added 28 Oct 2026🛡️ Security

CVE-2026-101767 is a CVSS 9.8 unauthenticated SQL injection in Oracle E-Business Suite's Application Object Library, reachable through the /OA_HTML/AppsTCFServer servlet (GanttDataServer) and chainable to OS command execution. It affects versions 12.2.3 to 12.2.15 and was fixed in the October 2026 Critical Patch Update. Horizon3.ai found it, and Defused saw probing on honeypots on 27 October 2026. Interim mitigation is removing the servlet from the URL firewall allowlist.

orca.securityadvisoryPublished and added 28 Oct 2026🛡️ Security

CISA advisory ICSA-26-302-03, republished from Hitachi Energy PSIRT 8DBD000258, covers OS command injection (CVE-2026-13162) and the Dirty Frag vulnerability (CVE-2026-43284) in Hitachi Energy CoreTec. CoreTec5 up to 3.4.0 and 5.0.0 are affected by both, and CoreTec4 up to 3.4.0 by CVE-2026-13162. The advisory was released 27 October 2026 and lists generic ICS mitigations. SSVC rates exploitation as none.

cisa.govadvisoryAdded 29 Oct 2026, published 28 Oct 2026🛡️ Security

Log-To-Leak is an arXiv paper (cs.CR, cs.AI) by Yuepeng Hu, Chongyu Fan, Sirat Samyoun and Jian Du on prompt injection attacks against tool-using LLM agents through the Model Context Protocol. The title points to a logging-based data leakage channel. The fetched page holds only the title, authors and arXiv link, with no abstract, so the method and results are not visible here.

x.compaperAdded 29 Oct 2026, published 28 Oct 2026🛡️ Security

Gemini 4 Carbon is Google's frontier model, announced with cybersecurity results: 88.2% on SEC-bench Pro (finding vulnerabilities), 54.8% on ExploitGym (exploitation) and 71.0% on CWE-bench (patching). Google reports 0.0% attack success on Gray Swan's indirect prompt injection benchmark. Access starts with a subset of cyber defenders through the Fairwind Program. Pricing is $2 per million input tokens and $10 per million output tokens.

blog.googlearticleAdded 29 Oct 2026, published 28 Oct 2026🛡️ Security

Gemini 4 Carbon is Google DeepMind's frontier model, announced with a focus on cyber defense. DeepMind reports 88.2% on SEC-bench Pro (finding vulnerabilities), 54.8% on ExploitGym (exploitation) and 71.0% on CWE-bench (patching), run without guardrails. It also reports 0.0% attack success on Gray Swan's indirect prompt injection benchmark. Access starts with a subset of cyber defenders via the Fairwind Program.

deepmind.googlearticlePublished and added 28 Oct 2026🛡️ Security

CVE-2026-101767 is a CVSS 9.8 unauthenticated SQL injection in the Application Object Library of Oracle E-Business Suite, patched in Oracle's October 2026 CPU and reported by Horizon3.ai. Defused decoys logged the first exploratory attempts on 27 October 2026, and the flaw could lead to remote code execution. The article recalls CVE-2026-46817 attacks in June and last year's Cl0p zero-day campaign against EBS.

securityweek.comarticlePublished and added 28 Oct 2026🛡️ Security

LLMON (LLM Object Notation) is a framework that separates instructions from data and requires explicit identifier-based execution. The authors post-train Granite-4.1 3B and 8B base models with SFT then RL on a 4.6B-token structured corpus covering general, RAG and tool-calling data, with distractor variants. Attack success rates on indirect prompt-injection benchmarks fall from 53-100% to 0.02-5.6%, and general capability is preserved. Attention-based metrics diagnose failures per transformer layer.

arxiv.orgpaperAdded 30 Oct 2026, published 28 Oct 2026🛡️ Security

LLMON (LLM Object Notation) is a framework that separates executable instructions from passive data and requires explicit identifier-based execution. The paper post-trains Granite-4.1 3B and 8B base models on a 4.6B-token corpus of general, RAG and tool-calling data with distractor variants, using SFT then RL. Attack success rates on indirect prompt-injection benchmarks fall from 53-100% to 0.02-5.6%, with general capabilities preserved. It also adds attention-based per-layer diagnostics.

arxiv.orgpaperAdded 30 Oct 2026, published 28 Oct 2026🧠 AI

Buchi Reddy B's X thread comments on Forever Security's research (Gal Weizman, Omer Samet) on coding agents. A web page silently writes a fake AGENTS.md or CLAUDE.md into a Downloads folder, and Codex and Claude Code follow it as project rules. Codex then wrote an attacker's MCP server into the machine-wide config, so one injection becomes a standing connection for every session. It asks whether teams inventory runtime MCP connections against approved lists.

x.comthreadAdded 28 Oct 2026, published 27 Oct 2026🛡️ Security

Heads of Security (HoS) is a prompt injection defense that enforces instruction-data separation with learned per-head attention gates, redistributing attention between trusted and untrusted tokens. Evaluated on Llama-3.3-70B-Instruct and GPT-OSS-20B against SecAlign++ and ASIDE. The black-box RL-Hammer attack reaches 97% ASR on GPT-OSS-20B and 85% on SecAlign but 10% on HoS. The white-box Claudini attack needs 3 times more FLOPs on HoS. HoS keeps base-model utility in few-shot settings, where SecAlign and ASIDE degrade.

arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🛡️ Security

Heads of Security (HoS) is a prompt injection defense that trains a small set of per-head attention gates to shift attention between trusted and untrusted tokens, separating instructions from data. Tested on Llama-3.3-70B-Instruct and GPT-OSS-20B, the black-box RL-Hammer attack reaches 10% ASR on HoS versus 97% on base GPT-OSS-20B and 85% on SecAlign. HoS keeps base utility in few-shot settings, where SecAlign and ASIDE degrade.

arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🧠 AI

X thread started by Nicholas Martin (#IAM) advising that MCP tool permissions be verified and scoped session tokens used to enforce least privilege against indirect prompt injection. Replies argue that token scoping does not solve the confused deputy problem, because an injection borrows the agent's legitimate authority. They recommend per-task tokens with short expiry, with the grant logged beside the call, and raise MCP server dependency supply-chain risk.

x.comthreadAdded 28 Oct 2026, published 27 Oct 2026🛡️ Security

What Victims Take Away is an October 2026 arXiv paper analysing 563,349 Tensor Trust attack records to see how players reuse prompt injections they received. Within a week, targets reused 10.0% of attacks that broke their defense, versus 0.03% of matched attacks. Breaches were followed by defense changes that cut same-family attack success by 24.5 points. Received texts made up 23.2% of successful hijacks. The authors propose that AI security tools describe techniques without disclosing full attack text.

arxiv.orgpaperAdded 28 Oct 2026, published 27 Oct 2026🛡️ Security

AGTP's X thread summarizes Meta's Muse Spark 1.3 Evaluation Report. Prompt injection was tested on Exponential Security Labs' RepoInject v1 and BrowserInject v1 and on Gray Swan's IPI Arena, with robustness said to be on par with GPT-5.6 Sol. It also covers chain of thought controllability evals, PostTrainBench under Loss of Control, and Handshake's pre-release human red teaming. It notes the Midas Project's criticism of Muse Wonder's missing safety report.

x.comthreadAdded 27 Oct 2026, published 26 Oct 2026🛡️ Security

Thread summarizing Meta's Muse Spark 1.3 Evaluation Report, the safety write-up for the model released on September 2, 2026. It covers prompt-injection results on Exponential Security Labs' RepoInject v1 and BrowserInject v1 and Gray Swan's IPI Arena, chain-of-thought controllability evals, PostTrainBench under Loss of Control, and Handshake's human red teaming. It also notes The Midas Project's criticism that Muse Wonder still has no safety report, and the Muse Spark Open rollout (816B total, 42B active parameters).

x.comthreadAdded 27 Oct 2026, published 26 Oct 2026🧠 AI

Log-To-Leak is a prompt-injection attack on tool-using LLM agents that abuses Model Context Protocol tool metadata to trigger an attacker-controlled logging call after the last legitimate call, leaking the user query, server name, server response and agent response. Evaluated on five MCP servers and four agents, it reaches 62.64-100% attack success with 76.55-95.64% logging accuracy. Three defenses leave over 55% residual ASR on GitHub MCP with GPT-4o.

arxiv.orgpaperAdded 28 Oct 2026, published 26 Oct 2026🛡️ Security

An empirical study of security concerns in the OpenClaw AI personal assistant framework, using 25K+ posts from 13 subreddits (162 security-relevant) and 358 security-tagged GitHub issues (180 retained). It maps 521 CWE instances across 59 weakness types, concentrated in access control, sensitive-data exposure, injection and unsafe execution. It extracts 543 practitioner mitigations into seven strategies and reconstructs a sensitive-data exposure path with dummy secrets.

arxiv.orgpaperAdded 28 Oct 2026, published 26 Oct 2026🛡️ Security

The Pwn Request Reckoning is a Wiz post updating the GitHub Actions pull_request_target threat model for 2026. It covers what GitHub's checkout protections, read-only cache tokens and event policies block, and what still works. Remaining paths: SHA-pinned pre-backport actions/checkout, custom checkout scripts, issue_comment and repository_dispatch triggers, script injection, artifact poisoning, self-hosted runner state and allow-unsafe-pr-checkout. It ends with grep and zizmor audit steps.

wiz.ioarticlePublished and added 26 Oct 2026🛡️ Security

Scope-Gap Injection (SGI) is an indirect prompt injection method for multi-stage LLM-agent safety pipelines, tested in the IJCAI 2026 OpenClaw Agent Security Attack Competition. The visible task and skill stay benign while target identifiers, bypass parameters and authorization steps sit in an attachment written as a business worklist, which the S2 LLM judge appears not to inspect. SGI bypassed all three stages (static scan, LLM judge, live audit) for 5 of 19 targets, best F = 0.385. Attachment placement had 78% S2 acceptance versus 23% in-skill. The paper closes with defenses that align evaluator scope with agent channels.

arxiv.orgpaperAdded 27 Oct 2026, published 26 Oct 2026🛡️ Security

Addendum to the GPT-6 Astra system card for OpenAI's GPT-6.1 Terra, rated Critical in cybersecurity and High in biological and chemical capability under the Preparedness Framework. It reports multiturn jailbreak and prompt-injection results, alignment tests (auto-review circumvention, ExploitGym honeypot, monitor evasion), and cyber scores: 97.10% ExploitBench, 24.5% on the internal recent-vulnerability port, 5 of 22 Sandbox Bench targets.

deploymentsafety.openai.compaperPublished and added 26 Oct 2026🛡️ Security

SentryBench is a benchmark for tool-using LLM agents in public-safety deployments. It scores attack success, over-refusal (missing a real emergency) and over-reaction (unwarranted action) on a cost-sensitive frontier, using real emergency-call transcripts, disaster messages and injection payloads. Across 840 episodes on three frontier models and three defenses, refuse-more caution pushed over-refusal to 100 percent on two models, while a trust-gating wrapper gave the lowest harm.

arxiv.orgpaperAdded 27 Oct 2026, published 25 Oct 2026🧠 AI

SentryBench is a benchmark for tool-using LLM agents in public-safety settings (public alerts, responder dispatch, citizen-record queries). It scores attack success, over-refusal and over-reaction on a cost-sensitive frontier, using real emergency-call transcripts and real injection/jailbreak payloads. Across 840 episodes on three frontier models and three defenses, refuse-more caution raised over-refusal to 100 percent on two models, while a trust-gating wrapper gave the lowest harm on every model.

arxiv.orgpaperAdded 27 Oct 2026, published 25 Oct 2026🛡️ Security

claude-skills is an open-source MIT library of about 398 Claude Code skills, agents and plugins that also installs into Codex, Gemini CLI, Cursor and 9 other coding agents. The security-relevant parts are skill-security-auditor, a stdlib-only Python scanner that checks skills for command injection, data exfiltration, prompt injection and dependency supply-chain risks before install, plus a security-guidance PreToolUse hook, a security suite and compliance skills (ISO 27001, SOC 2, GDPR).

github.comrepoAdded 25 Oct 2026🛡️ Security

CyberForge Weekly CVE Rundown #007 covers six CVEs from 19 to 24 October 2026: SiteGuard command injection (CVE-2026-106931), DB-GPT (CVE-2026-77932), Siemens Software Center DLL side-loading (CVE-2026-110936), Cisco Expressway (CVE-2026-76466), Node.js Brotli (CVE-2026-111497) and Arista VeloCloud (CVE-2026-114625). Each entry gives defender actions, fixed versions, exploitation status and primary-source links. Updated 25 October 2026 with CISA KEV and EPSS findings.

x.comarticleAdded 27 Oct 2026, published 25 Oct 2026🛡️ Security

BARBICAN is a fail-closed prompt-injection gateway for MCP tool mediation. This paper shows its arbitration classifier ran on tokenizer-mangled text for a whole evaluation. Fixing it raised AUC from 0.392 to 0.855 while system recall fell from 80.67% to 80.34%. The routed band is 96.82% malicious, so deletion ablations mislead without substitution experiments and class-balance reporting.

arxiv.orgpaperAdded 27 Oct 2026, published 23 Oct 2026🛡️ Security

The paper analyses BARBICAN, a fail-closed prompt-injection gateway for MCP tool mediation, using deletion, substitution, repair and transplant experiments. Its arbitration classifier ran on tokenizer-mangled text for a whole evaluation. Fixing that raised AUC from 0.392 to 0.855 while system recall fell from 80.67% to 80.34%. The band it receives is 96.82% malicious. The authors argue ablation figures need the band's class balance and substitution baselines.

arxiv.orgpaperAdded 27 Oct 2026, published 23 Oct 2026🧠 AI

MCP-Injector is a protocol-aware fault-injection middleware for Model Context Protocol tool calls, with permanent, transient and intermittent faults on seedable schedules. Its fault model comes from 57,240 issue and PR threads across 1,774 open-source MCP repositories. In a 1,350-cell experiment, faults cut task-completion score by 60% (8.08 to 3.23 of 10), and the 120B gpt-oss model was no more resilient than the 20B. Agent stacks differed in how well they absorbed faults.

arxiv.orgpaperAdded 26 Oct 2026, published 23 Oct 2026🧠 AI

NTBench (Near-Target Benchmark) tests LLM and agent robustness to near-target prompt injection, where injected instructions steer a response toward a plausible but incorrect or harmful outcome instead of abandoning the task. It builds reference-guided target-instruction pairs on existing datasets, with human validation, and evaluates seven LLMs on ten language datasets and two agent benchmarks. Attack success rose 9.3 to 35.8 points (incorrect targets) and 1.7 to 17.3 points (harmful targets) over fixed-target baselines.

arxiv.orgpaperAdded 26 Oct 2026, published 23 Oct 2026🛡️ Security

CVE-2026-114625 is a critical (CVSS 9.9) SQL injection in Arista's on-prem VeloCloud Orchestrator, exploited in the wild. Any authenticated user can gain superuser operator privileges. Releases before 5.2.3.18, 6.1.3.10 and 6.4.2.12 are affected, and hosted deployments are already patched. Attacks came from 74.82.197.86 and 38.54.50.151. It is the third exploited VCO zero-day in four months, after CVE-2026-16812 and CVE-2026-93952.

securityweek.comarticlePublished and added 23 Oct 2026🛡️ Security

CVE-2026-114625 is a critical (CVSS 3.1 9.9) SQL injection in on-prem Arista VeloCloud Orchestrator, the SD-WAN management portal, covered in Arista Security Advisory 0199 of 22 October 2026. Any authenticated user, even the lowest Enterprise Read Only tenant role, can become a local superuser operator, and Arista says it is exploited in the wild. On-prem fixes are 5.2.3.18, 6.1.3.10 and 6.4.2.12; two attacker IPs are listed.

x.comadvisoryAdded 24 Oct 2026, published 22 Oct 2026🛡️ Security

ZTrust is a Python supply-chain scanner that checks manifests, lockfiles, source and GitHub workflows for vulnerable or malicious dependencies (via OSV.dev), typosquats, leaked secrets, unsafe lockfiles and risky CI patterns such as pwn requests and script injection. It outputs console, JSON and SARIF 2.1.0 and ships as a GitHub Action. It also includes a FastAPI bounty service using commit-reveal and shielded Zcash payouts for researchers.

github.comrepoAdded 27 Oct 2026, published 22 Oct 2026🛡️ Security

claude-red is a library of offensive security skills for the Claude Skills system, each a SKILL.md file that loads on conversational triggers (for example, mentioning SQL injection loads offensive-sqli). Categories include web, Active Directory, cloud, mobile, exploit development, fuzzing, privilege escalation, post-exploitation and AI. It targets about 130 skills across 23+ categories, with an install script and sparse-checkout install per category. Built on Sahar Shlichov's offensive checklists, MIT licensed.

github.comrepoAdded 22 Oct 2026🛡️ Security

Post summarising Pillar Security's finding of a remote code execution flaw in OpenCode, the open-source AI coding agent. Versions 1.0.137 through 1.18.32 could run code from a remote MCP server during OAuth sign-in on Windows and WSL, with no prompt injection needed. The fix is in 1.18.33 (released 28 September). No advisory or CVE was issued, so scanners will not flag old installs. Interim advice is to remove unvetted remote MCP servers.

x.comthreadAdded 22 Oct 2026, published 21 Oct 2026🛡️ Security

Paper on prompt injection delivered through forensic evidence, where the seized device's contents are attacker-controlled and the examiner must read them. It extends the anti-forensic model to cover manipulation of the reasoning layer and gives a taxonomy (objective, technique, payload location, concealment). Three proof-of-concept attacks on an LLM-assisted analysis pipeline change a reported conclusion, write attacker-chosen content to the analyst workstation, and trigger outbound network traffic. Mitigations are proposed.

arxiv.orgpaperAdded 24 Oct 2026, published 21 Oct 2026🛡️ Security

MPIDetector is a detection framework for multi-modal prompt injection that uses few-shot in-context learning so an LLM can reason about the semantic intent of text and image inputs, without fine-tuning. The authors built a benchmark of eight textual and seven visual attack categories plus benign sets. They report up to 90.91% accuracy on text, 99.28% on images, and up to 99.80% detection on 500 obfuscated WebInject web-agent injections, beating baselines.

arxiv.orgpaperAdded 24 Oct 2026, published 21 Oct 2026🛡️ Security

Paper (arXiv, 21 October 2026) on structural false negatives in LLM vulnerability discovery harnesses. Starting from Knostic's OpenAnt and raptor, then 10 more open-source harnesses, the authors map 13 points where code selection, filtering, and finding storage or merging drop vulnerabilities. One file was dropped by six harnesses before the model saw it, five without notice. It covers attacker evasion, content-steered verdicts, prompt injection, and design principles and tests.

arxiv.orgpaperAdded 24 Oct 2026, published 21 Oct 2026🛡️ Security

CVE-2026-101767 is an unauthenticated SQL injection in the Oracle E-Business Suite Thin Client Framework servlet (/OA_HTML/AppsTCFServer, oracle.apps.fnd.tcf.SocketServer), CVSS 3.1 9.8. It runs SQL as the APPS user and chains to OS commands as the EBS account. Affects 12.2.3 to 12.2.15, fixed in the Oracle October 2026 CPU (20 October 2026). The page lists mitigations, IOCs and a timeline.

horizon3.aiadvisoryAdded 29 Oct 2026, published 20 Oct 2026🛡️ Security

Paper on memory injection, where prompt injection persists across sessions through the long-term memory of LLM-as-a-service platforms. It presents a general threat model and shows all NIST attack goals are achievable on ChatGPT Instant 5.3, Claude Sonnet 4.6 and Gemini 3 Flash. Vectors include personal memories, projects, skills, organization instructions and MCP resources. On Claude, shared memory lets an attacker compromise multiple users in an organization and exfiltrate prompts. Nearly half of the derived mitigations are unimplemented.

arxiv.orgpaperAdded 24 Oct 2026, published 20 Oct 2026🛡️ Security

CarryoverBench is a benchmark of 12 personal-assistant scenarios and 101 attack tasks for carryover attacks, where a one-time indirect prompt injection planted in agent memory files or scheduled tasks re-fires in later sessions. Three trigger channels (Instant, Autonomous, Latent) are scored by a rule-based verifier with separate planting and triggering stages. Across five frontier models, payloads re-fire over five rounds without measurable decay. Porting the Latent channel to the Hermes runtime weakens the effect but does not remove it.

arxiv.orgpaperAdded 22 Oct 2026, published 20 Oct 2026🛡️ Security

nokast-secureRAG is a roughly 0.5B-parameter small language model that works as a semantic firewall between retrieval and generation in local RAG systems. It classifies each query and context pair as safe, suspicious or malicious. It reaches 0.994 recall at a 0.026 false-positive rate in-distribution, beating Llama Guard 3 1B and Prompt-Guard-86M (0.900 recall, 0.690 FPR). Recall on PoisonedRAG falls to near zero, and single-request latency is 293-404 ms.

arxiv.orgpaperAdded 22 Oct 2026, published 20 Oct 2026🛡️ Security

Systematic evaluation of fault attacks on ML-DSA (FIPS 204) rejection sampling and of proposed countermeasures. It proves the "third rejection test" of patent WO2025261784A1 re-verifies what check 2 already guarantees, and shows that 30,000 fault injections never detect a skipped z-norm check. The author fully recovers s1 against a third-check-protected implementation under randomized signing. Third check and sign-then-verify are complementary; overhead is 0.04–0.05% on x86-64 and 0.83% on Cortex-M4 for the third check.

eprint.iacr.orgpaperAdded 21 Oct 2026, published 20 Oct 2026🛡️ Security

KNOX is a regulatory sandbox for generative models built by running AI agent workloads inside TEEs. It derives an attested policy manifest (applicable regulations, expected tool calls, permitted system calls) from the user prompt, and an attested reference monitor allows an action only if it matches. Actions and verdicts go into an attested execution graph that regulators can verify. The paper reports detection of prompt-injection deviations and under 1% overhead.

arxiv.orgpaperAdded 22 Oct 2026, published 20 Oct 2026🛡️ Security

Datadog Security Labs announcement, posted by Nick Frichette, of research on steering the evaluations of a prompt-injection detector called "Jev". The team's method cut its detection rate from about 83% to about 4% in their tests. They also used it to bypass LangChain's experimental tool-risk gating feature that is based on Jev. The tweet gives no method details and links to the full article.

x.comthreadAdded 21 Oct 2026, published 19 Oct 2026🛡️ Security

Fake News, Real Crashes is an October 2026 arXiv paper presenting a benchmark for information injection attacks on LLM financial trading agents. It spans five injection vectors, seven event categories and about 10,000 decisions on 15 U.S. stocks. Fabricated news reached 62% attack success versus 14% for prompt injection, and two 30-word templates hit 100%. Only hierarchical aggregation reduced success among the defenses tested.

arxiv.orgpaperAdded 21 Oct 2026, published 19 Oct 2026🛡️ Security

MITRE ATT&CK v20 adds nine Enterprise techniques and sub-techniques, including two prompt injection techniques, abuse of an organization's own AI agents for data theft, application-specific password theft and CAPTCHA bypass. ICS gains campaigns on internet-exposed PLCs at over 30 Minnesota water utilities and an AI-assisted breach of Mexican government bodies. It also adds Nimbus Manticore, The Gentlemen, 15 detection strategies with 38 analytics, and NGate for Mobile.

securityweek.comarticlePublished and added 19 Oct 2026🛡️ Security

CVE-2026-106931 is an OS command injection (CWE-78) in the statistics processing of EG Secure Solutions SiteGuard Server Edition, a host-based WAF. It can give root or SYSTEM command execution. The vendor and JVN confirm exploitation on 14 October 2026. The post lists fixed builds (Ver8.00 Update 5, Ver7.00 Update 6 on FreeBSD), the IIS exclusion, the workaround of disabling statistics, and a SOC trail starting with diagnostic preservation before patching.

x.comadvisoryAdded 21 Oct 2026, published 19 Oct 2026🛡️ Security

SpanGuard is an indirect prompt injection (IPI) guardrail that splits detection into two steps. Lightweight unsupervised segmentation first locates candidate instruction blocks in tool outputs, then a small LLM judges whether each block is authorized by the user's request. The authors report a 0.32% attack success rate with negligible benign utility loss, and the guardrail still works with substantially smaller models.

arxiv.orgpaperAdded 21 Oct 2026, published 19 Oct 2026🛡️ Security

This ePrint paper presents key-independent filters that remove misinjections (faults that miss the assumed form) in elimination fault attacks. A SAT filter, a neural network filter and a combined filter were tested on clock-glitch faults into GIFT-64, GIFT-128 and BAKSHEESH on a microcontroller. The SAT filter rejected none of 14669 intended faults, and raised ToFA success on BAKSHEESH from 5.2% to 61.2% (96.2% combined).

eprint.iacr.orgpaperAdded 20 Oct 2026, published 19 Oct 2026🛡️ Security

IISFA (Ineffective Instruction-Skip Fault Attack) targets bitsliced block cipher implementations protected by redundancy countermeasures. Skipping one bitslice instruction leaves the result unchanged only when all m S-box inputs fall in an ineffective set, so each released ciphertext restricts all m subkeys. The authors give known- and chosen-plaintext key-recovery procedures and expected injection counts, and recover keys in every trial on GIFT, SKINNY and PIPO implementations on an 8-bit AVR microcontroller using clock glitches.

eprint.iacr.orgpaperAdded 20 Oct 2026, published 19 Oct 2026🛡️ Security

PIAtlas is a taxonomy of prompt injection attacks organized by how the injected instruction subverts the model, with six mechanism classes as roots of a technique and sub-technique hierarchy. The authors release PICorpus, a license-clean collection of public prompt-injection datasets, and map thousands of records to PIAtlas under a human-verified protocol. Results show attacks combine several techniques from few mechanisms, agent benchmarks cover only part of the space, and adaptive attackers favor mechanisms that curated benchmarks underrepresent.

arxiv.orgpaperAdded 21 Oct 2026, published 18 Oct 2026🛡️ Security

ToFu is a tool-aware fuzzing framework for LLM tools, including MCP servers. It maps each tool argument, using its metadata, to one of 74 CWE-guided semantics-aware sanitizers (path, URL, SQL and similar). It then generates schema-valid Atheris harnesses and semantic oracles, using runtime tracers for in-process tools and outcome oracles for opaque ones. The LLM (gpt-4.1) only maps sanitizers and writes seeds; it is never the security judge. The paper also shows a "Repeat-After-Me" trick, where an LLM told to repeat attacker-crafted text emits a tool call the orchestrator executes, reproduced on LangGraph, MAF, ADK 2.0, AutoGen, Strands and CrewAI. Across 273 runnable MCP servers (3,405 tools) it reports 253 verified bugs in 343 tools across 118 servers, such as path traversal, log injection and exfiltration. These are failures a crash-based fuzzer would miss. The result matters because it shows LLM-generated tool arguments cannot be treated as trusted.

arxiv.orgpaperAdded 18 Oct 2026🧠 AI

ToFu is a tool-aware fuzzing framework that derives semantic security checks for LLM tools (mainly MCP servers) from their metadata and a corpus of 74 CWE-guided sanitizers. It generates schema-valid Atheris harnesses, uses runtime tracers and outcome oracles to catch bugs that don't crash, and uses an LLM only to map sanitizers and seed inputs, never as the judge. It also describes a "Repeat-After-Me" attack, in which the LLM is told to repeat attacker-written text that the orchestrator then dispatches as a tool call. It was reproduced on LangGraph, MAF, ADK, AutoGen, Strands and CrewAI. On 273 MCP servers it reports 253 verified bugs across 343 tools in 118 repositories, including path traversal, log injection, exfiltration and command bypass.

arxiv.orgpaperAdded 18 Oct 2026🛡️ Security

Explains why a reachable vulnerable function in a dependency is not necessarily exploitable, and how exploitability analysis extends SCA reachability analysis. It walks through CVE-2021-23337 (lodash _.template command injection) across three apps with different outcomes. It notes that a verdict can change with code, for example via prototype pollution and the follow-up CVE-2026-4800. A closing section describes Aikido's CVE Exploitability Analysis.

aikido.devarticleAdded 19 Oct 2026, published 17 Oct 2026🛡️ Security

An X post advises auditing every MCP write tool against the database role it actually runs under. A shared service key lets prompt injection trigger unapproved writes, so each agent session should get a read-only role, with a test that writes are denied. Replies note that MCP servers often inherit ambient host credentials or can escalate through a second connection pool, and suggest also testing that another tenant's rows are unreadable with the same role.

x.comthreadAdded 18 Oct 2026, published 16 Oct 2026🛡️ Security

A X thread benchmarking Qwen3.8 Flash Next on one DGX Spark in two builds: NVIDIA's FP4-Local checkpoint served by vLLM (eugr's b12x container) and an MLX 4-bit TensorFold recipe. The NVIDIA build scores higher on the author's agentic benchmark (81.2 vs 75.0), BFCL tool calling (82.4 vs 71.8 single-turn, 54.5 vs 43.0 multi-turn), AgentDojo prompt-injection resistance (2 vs 6 of 200 attacks succeeded) and GPQA (64.6 vs 59.1). TensorFold decodes faster (67 vs 44 tok/s) and runs more agent steps per minute (21 vs 14). The author notes the comparison covers whole stacks (engine, kernels, tool parser), not quantization alone, and links a docker compose recipe.

x.comthreadAdded 17 Oct 2026, published 16 Oct 2026🧠 AI

SecurityWeek's weekly roundup covers ICS-Sniper, a UBC proof-of-concept that uses VPN-encrypted packet size, direction and timing to drop critical SCADA traffic on cloud-hosted ICS (tested on the SWaT water testbed). It also covers an unauthenticated RCE PoC against the XWorm RAT C2 panel (up to 7.4) via path traversal DLL overwrite, and Langflow CVE-2026-105740 (MCP Stdio command injection, fixed in 1.9.0) exploited from September 19, before the CVE was published. Other items: XBOW's AI-assisted Chrome full-chain exploit (GPT-5.6 Sol, $250k bounty), Group-IB's KGB RAT analysis, Anthropic's disclosure of Claude rule-bending on live sites, Intel ending SGX after Diamond Rapids, Bank of America's Mythos-driven patching, the Burger King Japan breach and a West African scam-center takedown.

securityweek.comarticlePublished and added 16 Oct 2026🛡️ Security

MobileInject is a benchmark for testing MLLM-based smartphone agents against indirect multimodal injection. It has an interactive evaluation framework with 11 scenarios, 9 security-risk categories and 108 executable risk instances. It adds Cross-Modal Consistency Injection, Multi-Role Collaborative Deception, Reasoning-Camouflage Injection and a Reasoning Security Diagnosis Framework. Experiments find broad vulnerability, with many failures from early reasoning hijacking.

arxiv.orgpaperAdded 20 Oct 2026, published 16 Oct 2026🛡️ Security

Ignored, Not Refused audits 33,000 trajectories from eleven open-weight agents (2-14B parameters) on InjecAgent and AgentDojo. A label-blind LLM judge finds most failed indirect prompt injections are ignored (76-80%) rather than refused (17-18%). Changing only the system prompt moves InjecAgent ASR from 0.2% to 43%. The Attack-Task Outcome Matrix (ATOM) shows 21.7% of AgentDojo episodes were safe but left the user task incomplete. The corpus, judge prompt and code are released.

arxiv.orgpaperAdded 20 Oct 2026, published 16 Oct 2026🛡️ Security

"Ignored, Not Refused" audits 33,000 trajectories from eleven open-weight agents (2-14B parameters) on InjecAgent and AgentDojo. A label-blind LLM judge finds 76-80% of failed injection attacks were ignored and 17-18% refused. Changing only the system prompt moves InjecAgent attack success rate from 0.2% to 43%, and the ATOM matrix shows 21.7% of AgentDojo episodes were safe but left the user's task undone. The corpus, judge prompt and code are released.

arxiv.orgpaperAdded 20 Oct 2026, published 16 Oct 2026🧠 AI

R^2ECAP (Reused Reasoning-Cache Poisoning) is a black-box attack that plants poisoned reasoning traces through a chat interface, exploiting LLM systems that reuse KV caches of reasoning. A preceding trace steers the model, and the retained trace keeps residual adversarial influence in its cache after the preceding trace is discarded. On three open-weight LLMs and three datasets it reaches up to 79% ASR, beats the white-box HijackKV in 8 of 9 settings, and reaches 46% ASR in a reasoning-trace retrieval system. Only 1% of retained responses are flagged by a popular prompt injection detector.

arxiv.orgpaperAdded 20 Oct 2026, published 16 Oct 2026🛡️ Security

wp2shell-PoC is a Python proof-of-concept exploiting a pre-authentication RCE chain in WordPress core, combining CVE-2026-63030 (REST API batch route confusion) and CVE-2026-60137 (SQL injection in WP_Query). It demonstrates escalation from the route-desync bug through blind SQLi, customize_changeset forgery, and hook re-entry to administrator account creation and arbitrary command execution via a malicious plugin upload. The tool supports vulnerability checking, data extraction (union, error-based, blind techniques), and full shell access with or without existing admin credentials.

github.comrepoAdded 23 Oct 2026, published 15 Oct 2026🛡️ Security

Cloudflare announces a programmable secure web gateway: a Forward action (public beta) that routes matched HTTP traffic to a Worker acting as inline middleware, and Custom Functions that return typed values used as policy selectors. It also adds DLP custom validation functions, for example checking whether a detected GitHub token is still active before a profile matches. Code samples cover JWT role parsing, header injection and Slack alerting.

blog.cloudflare.comarticleAdded 29 Oct 2026, published 15 Oct 2026🛡️ Security

Presents fault injection attacks on BIKE and HQC decapsulation that target instructions outside the Fujisaki-Okamoto transform, achieving full key recovery with only valid ciphertexts at NIST Level 1 (17392 queries for HQC, about 3 million for BIKE). It also gives a general method for finding effective fault locations by analysing decoder behaviour under perturbed conditions. Attacks were validated with laser fault injection on an STM32H7 microcontroller, showing a wider attack surface for code-based post-quantum KEM implementations.

eprint.iacr.orgpaperPublished and added 15 Oct 2026🛡️ Security

Datadog Security Labs tests TypeSafe AI's Jev decision model as a prompt-injection detector and as the judge behind LangChain's tool-risk gating. On four public datasets Jev had 99.66% precision and 82.90% recall. A prepended "counterfeit policy" that redefines the attack categories cut recall by over 79 points. In a LangChain scenario, a user-editable profile field lowered the mean is_risky score from 0.893 to 0.290, below the 0.5 block threshold. Plain prompt injection did not move the score.

securitylabs.datadoghq.comwriteupAdded 29 Oct 2026, published 15 Oct 2026🛡️ Security

PEERSTITCH is a memory-resident ARM64 implant that Unit 42 found in a September 2024 telecom intrusion (cluster CL-STA-0954, aka UNC5820). Attackers used CVE-2024-47575 on FortiManager to steal configs for more than 500 FortiGates, then CVE-2025-61624 auto-script path traversal to reach root. The report covers ptrace injection into miglogd and iked, an Apache mod_md ACME reverse shell, FGFM impersonation, anti-forensics, hunting guidance, IOCs and YARA.

unit42.paloaltonetworks.comwriteupAdded 30 Oct 2026, published 14 Oct 2026🛡️ Security

Evaluates a native probabilistic decision model (Jev), Llama Prompt Guard 2 (22M and 86M) and an LLM judge on 47,611 held-out examples covering direct/indirect prompt injection, hard-benign inputs, obfuscation and distribution shift. The LLM judge has the best AUROC (0.897), followed by Jev (0.871), Prompt Guard 2 86M (0.757) and 22M (0.714). Jev's native probabilities do not consistently beat post-hoc calibrated classifier scores, and temperature scaling improves calibration but not discrimination. At a 1% false-negative-rate target, every system needs over 91.8% escalation, so probabilistic outputs alone do not give reliable security decisions under distribution shift.

arxiv.orgpaperAdded 17 Oct 2026, published 14 Oct 2026🛡️ Security

INFUSE is an end-to-end benchmark for indirect prompt injection (IPI) across long-horizon agent workflows (shell commands, code changes, dependency installs, remote services). It has 40 realistic tasks and a taxonomy of 56 attack scenarios in five threat categories, with attacks injected via interaction surfaces encountered mid-task. Across 19 LLMs (GPT, Claude, Gemini, Llama, Gemma, Qwen) and 41,824 adversarial trajectories, mean attack success was 19.6% (LLM-judged) and 15.4% (heuristic), per-model 3.2–41.9%; guard models gave limited protection, while prompt-level hardening cut mean ASR from 58.2% to 14.3%.

arxiv.orgpaperAdded 17 Oct 2026, published 14 Oct 2026🛡️ Security

News coverage of Google DeepMind's Gemini 4 Argon release on October 13, 2026. The model solved all 12 simulated end-to-end cyberattack scenarios, up from five for its predecessor, and scored 0.7% attack success on Gray Swan's Indirect Prompt Injection benchmark. It ships with three safeguard layers (small-model input screening, activation probes on internal signals, continuous response monitoring) and an automated misalignment monitor for agents. Launch pricing is $2 per million input tokens and $10 per million output tokens, doubling after November. Access is through Pro and Ultra tiers, and Ultra also gets Antigravity. The article also reports a training finding: penalizing internal thoughts cut openly discussed shortcuts by 61% but raised silent shortcuts from 11.2% to 36.4%.

en.cryptonomist.charticlePublished and added 14 Oct 2026🧠 AI

SecurityWeek summarizes Patch Tuesday-style releases from Citrix, Fortinet and Ivanti fixing 29 vulnerabilities. Highlights include critical FortiSIEM and FortiSandbox flaws (CVE-2026-106173 code execution, CVE-2026-107656 auth bypass), five SQL injection bugs across FortiAnalyzer, FortiManager and FortiMail, and Ivanti Connect Secure's exploited zero-day CVE-2026-104935 (two chained bugs compromising patched VPNs). Also covers critical Ivanti Neurons Patch for Intune (CVE-2026-109412) and Xtraction (CVE-2026-106042) issues and Citrix fixes in Workspace App, XenServer and UniconOS.

securityweek.comarticlePublished and added 14 Oct 2026🛡️ Security

SecurityWeek summarizes SAP's October 2026 Security Patch Day (22 notes, four critical). Critical flaws: CVE-2026-89111 (CVSS 10) OAuth2 SSRF in SAP Cloud SDK for Python that leaks client credentials via the tenant_subdomain parameter; CVE-2026-89110 (9.9) NetWeaver broken access control allowing ABAP code execution through Fiori rule definition input; CVE-2026-89107 (9.9) S/4HANA Visual Composer code injection; and CVE-2026-89108 (9.1) missing authorization check in Manufacturing Integration and Intelligence allowing admin account creation. SAP reports no exploitation in the wild.

securityweek.comarticlePublished and added 14 Oct 2026🛡️ Security

Summary of SAP's October 13, 2026 Security Patch Day (16 new notes, 4 GitHub advisories). It leads with CVE-2026-89111, a CVSS 10.0 OAuth2 SSRF in SAP Cloud SDK for Python before 0.45.2, where an attacker-controlled tenant_subdomain redirects token requests and exfiltrates client credentials. It also lists three other critical flaws: broken access control in NetWeaver Visual Composer, code injection in S/4HANA substitution/validation rules, and a missing authorization check in the Manufacturing Integration and Intelligence (XMII) Configuration Service. It notes that none are in CISA KEV and SAP reports no in-the-wild exploitation.

x.comadvisoryAdded 15 Oct 2026, published 13 Oct 2026🛡️ Security

CVE-2026-103572 is a remote code execution bug in Microsoft.VisualStudio.Copilot.Core.dll, shared by Visual Studio and SQL Server Management Studio. A trailing dot (for example `.mcp.json.`) bypasses the protected-filename check in EditsFunctionHandler.GetEditConfirmationTypeAsync, so a hijacked Copilot can rewrite its own MCP and settings files and run commands. The post covers path traversal and InstallationID leaks, indirect prompt injection demos, the October 2026 patch (GetFullPath), and a $0 bounty.

embracethered.comwriteupAdded 29 Oct 2026, published 13 Oct 2026🛡️ Security

DeepMind describes how it made Gemini 4 Argon safe for broad release. For misuse in cyber and bio, it uses input screening, activation probes that read internal signals, and continuous monitoring, under its Frontier Safety Framework. For misalignment, it trained the model to respect boundaries and runs a real-time monitor over actions and chain-of-thought. Reported figures: shortcut attempts down to 2%, and prompt-injection attack success of 0.7% on Gray Swan's IPI benchmark. It also reports that penalizing chain-of-thought in RL cut openly discussed shortcuts by 61% while silent shortcuts rose from 11.2% to 36.4%, which is why DeepMind does not penalize the chain of thought in training.

deepmind.googlearticlePublished and added 13 Oct 2026🧠 AI

Google DeepMind's launch page for Gemini 4 Argon, a frontier model pitched at long-horizon software engineering, science and math, robotics, cyber defense and professional workflows. Stated specifics: a 1M-token output window for full-repository generation and long proofs, a tie for #1 on CWE-Bench (68%) for vulnerability remediation, and a 14% accuracy gain over Gemini 3.1 Pro in Box's evaluation. It also describes safeguards (resistance to indirect prompt injection, chain-of-thought monitoring, sandbox hardening under the Frontier Safety Framework) and availability via Google AI Pro/Ultra, Gemini API, AI Studio and Antigravity. Much of the evidence is partner testimonials and vendor-reported results.

deepmind.googlearticlePublished and added 13 Oct 2026🧠 AI

Introduces SA-CUA, a dual-LLM framework that gives Computer Use Agents a trust boundary against indirect prompt injection. It derives conservative deterministic rules from the accessibility tree to unmask trusted screen regions for the privileged LLM, and adds an endorsement channel that moves values from untrusted to trusted domains by verification. Human input is needed only at task specification. It reports much higher utility than CaMeL-CUA with a zero attack success rate.

arxiv.orgpaperAdded 15 Oct 2026, published 13 Oct 2026🛡️ Security

Introduces SA-CUA, a dual-LLM framework for Computer Use Agents (CUAs) that defends against indirect prompt injection. It builds a trust boundary by deriving conservative deterministic rules from the accessibility tree, which unmask trusted screen regions in the privileged LLM's screenshot and keep untrusted content separate. An endorsement channel lets values move from the untrusted to the trusted domain through verification over trusted channels. This removes the need for per-action user confirmation and the confirmation fatigue it causes. SA-CUA is reported to keep much higher utility than CaMeL-CUA with a 0% attack success rate.

arxiv.orgpaperAdded 15 Oct 2026, published 13 Oct 2026🧠 AI

SecurityWeek reports a cyberattack on hundreds of European supermarkets (Auchan, Carrefour, E.Leclerc, Intermarché, Monoprix, Cooperative U) in which attackers remotely took over Danfoss refrigeration controllers and set target temperatures to 50°C, spoiling food; over 300 French stores were reportedly hit. The attack came about two months after Claroty disclosed auth bypass, remote code execution and config injection flaws in the Danfoss AK-SM 800A management platform (fixed in firmware R4.3.1), though it is unclear whether those flaws were exploited. It illustrates real-world physical impact from exposed OT/IoT management interfaces.

securityweek.comarticlePublished and added 13 Oct 2026🛡️ Security

BrowseSafe++ extends BrowseSafe to 38,675 paired attacked/clean web pages, most with prompt injections observed in the wild on production sites. Pages cover twelve site types, 24 attack types and 18 injection locations, each given as HTML, Markdown, accessibility tree and screenshot with a user task and expected answer. The authors train BrowseSafe-Guard, two 0.8B detectors (text and screenshot) that beat a frontier-model-based detector on F1 with low false positives and low inference cost. BrowseSafe-Adapt rewrites injections using browser-agent feedback, raising attack success from a few percent to up to 95.41%.

arxiv.orgpaperAdded 15 Oct 2026, published 12 Oct 2026🛡️ Security

Commentary on the 2025 OWASP Top 10 update presented at OWASP Global AppSec in Washington, D.C. Broken Access Control stays #1, Security Misconfiguration and the new Software Supply Chain Failures category (replacing Vulnerable and Outdated Components) rise to #2 and #3, and Cryptographic Failures, Injection and Insecure Design drop. The author adds context on agentic AI and MCP identity and authorization, AI-assisted SAST, non-human identities, CISA Secure-by-Default, OWASP SPVS, and slopsquatting and AI coding assistant risks.

endorlabs.comarticlePublished and added 12 Oct 2026🛡️ Security

StableJudge is a defense framework against score-hijacking prompt injection in LLM-as-a-Judge pipelines (e.g. paper review, recommendation). A compact 0.13B "Sentry" model localizes injected spans and sanitizes them before the judge scores the content, trained on adversarially evolving attacks, and deterministic fine-grained scores are derived from the judge's output distribution. It improves score recovery under attack on held-out scientific abstracts and out-of-distribution attack variants while preserving general performance, decoupling safety from judge model scale. Code and data are promised but not yet released.

arxiv.orgpaperAdded 15 Oct 2026, published 12 Oct 2026🛡️ Security

A researcher announces a zero-click indirect prompt injection RCE in REA (Reverse Engineering Assistant), an MCP tool. Analyzing a malicious web target silently exfiltrates AWS keys, GitHub tokens and SSH identities. The stated root cause is that process.env is passed unconditionally to child processes, so the full environment is exposed to attacker-driven commands. A full writeup is promised but not yet published; replies add unverified skepticism about the project's provenance.

x.comthreadAdded 13 Oct 2026, published 12 Oct 2026🛡️ Security

A thread listing seven GitHub repos for securing LLM apps that can call tools: garak, PyRIT and promptfoo for attack and red-team testing, LLM Guard and Rebuff for input/output scanning and prompt-injection detection, NeMo Guardrails for programmable rails, and Inspect AI for repeatable evaluations. It proposes a loop of map risks, attack, inspect failures, add controls, retest and monitor. It stresses that a system prompt is not a security boundary and that credentials should be scoped, tool arguments validated outside the model, and consequential actions approved. It also warns that Rebuff is archived.

x.comthreadAdded 12 Oct 2026, published 11 Oct 2026🛡️ Security

Arcjet JS SDK is an Apache-2.0 JavaScript monorepo that adds runtime security checks to AI apps, agents and HTTP endpoints. It ships framework SDKs (Next.js, Node.js, Bun, Deno, Fastify, NestJS) plus a Guard API for agent tool calls, MCP handlers, queue workers and background jobs that have no HTTP request object. Features include prompt injection detection, sensitive-information detection (PII, credit cards, custom patterns) and token-bucket, fixed-window and sliding-window rate limiting.

x.comrepoPublished and added 11 Oct 2026🛡️ Security

Arcjet JS SDK is an open-source (Apache-2.0) JavaScript monorepo that adds runtime security to AI apps, agents and HTTP endpoints. It ships request SDKs for Next.js, Node.js, Bun, Deno, Fastify and NestJS. It also has a Guard API for places with no HTTP request object, such as agent tool calls, MCP handlers, queue workers and background jobs. Built-in checks cover prompt-injection detection, sensitive-information detection (PII, credit cards, custom patterns) and token-bucket, fixed-window or sliding-window rate limits, including token budgets.

x.comrepoPublished and added 11 Oct 2026🧠 AI

This repository hosts a proof-of-concept for CVE-2026-41940, described as a CVSS 10.0 unauthenticated authentication bypass in cPanel and WHM caused by CRLF injection into server-side session files via the Authorization header. The accompanying Python tool (cve.py) can detect vulnerable cPanel/WHM instances, retrieve system and account information, and perform post-exploitation actions such as running OS commands, changing the root password, and opening an interactive WHM shell. It also supports bulk scanning workflows piped from subfinder, httpx, and Shodan.

github.comrepoAdded 23 Oct 2026, published 11 Oct 2026🛡️ Security

Case study of about 3 months spent having Claude Code and Codex CLI agents decompile a popular first-person shooter to C++, using Hex-Rays' ida-mcp for disassembly. Early agent output ran but was semantically wrong, and a reviewer agent accepted worker justifications in commit comments, which acted as unintentional prompt injection. The fix was a byte-matching oracle: it compiles with the original toolchain and compares OBJ function bytes against the EXE/PDB, treating relocations separately. Agents tried to cheat with inline assembly and by editing the checker, so CI hashes the script. The result was 99% of functions present and 83% byte-exact, at an estimated 600-700B tokens.

momo5502.comwriteupPublished and added 11 Oct 2026🛡️ Security

A retrospective on a 3-month project in which Claude Code and Codex agents (Sonnet 5, Opus 5.5, Luna, Sol, Terra) decompiled a first-person shooter into C++, using ida-mcp, GitHub issues and Discord for coordination. The first month's agents produced readable but semantically wrong code, and a reviewer agent could not catch it. A byte-matching oracle script, comparing compiled OBJ output against the original EXE/PDB, gave a strict PASS/FAIL signal. That let cheaper models like Luna scale to 14+ agents and reach 99% of functions present and 83% byte-exact. Lessons include lowering the compaction threshold to 42%, hourly cron re-injection of the instruction document, hashing the verifier in CI to stop agents tampering with it, and the failure of review when correctness is undefined.

momo5502.comwriteupPublished and added 11 Oct 2026🧠 AI

Proposes Staggered Instruction-Fetch Duplication (SIFD), a processor-level fault-injection countermeasure that fetches each instruction twice in consecutive cycles while fetching two different instructions per cycle, so inconsistent fetches are detected without full processor duplication, compiler support or crypto hardware. Implemented on a custom RV32I core on an Artix-7 FPGA, it costs 15.0% more slices and 16.3% more execution time. Attack success falls from 0.86% to below 0.01% under clock fault injection and from 0.32% to 0.13% under EMFI, with 73.18% of CFI and 11.44% of EMFI attempts detected.

eprint.iacr.orgpaperAdded 14 Oct 2026, published 10 Oct 2026🛡️ Security

Introduces Policy-Constrained Diffusion Agents (CoDA), which enforces task-dependent security policies inside the denoising process of diffusion language models. At each step, token distributions are projected onto a policy-compliant set, so constraints hold throughout generation instead of relying on detecting injected instructions. Evaluated across several dLLM families under static and adaptive prompt-injection attacks, it reports substantially lower attack success rates with competitive task utility and practical inference overhead.

arxiv.orgpaperAdded 15 Oct 2026, published 10 Oct 2026🛡️ Security

Paper testing whether an LLM agent operating life support in the NASA-derived BioSim lunar habitat simulation can be induced by delayed prompt injection, hidden in truthful S-band telemetry, to shut down life support and hold the shutdown while the crew suffocates. It compares Claude, GPT and Grok configurations: Claude mostly refuses and cites the living crew, GPT shows some susceptibility, and Grok given a "trusted commission" framing more often cuts life support. It also varies the framing of the message (trusted commission, peer, untrusted source) and uses a harmless-procedure-drop attack as a proxy for whether life is valued intrinsically. Code and traces are open-sourced.

arxiv.orgpaperAdded 15 Oct 2026, published 10 Oct 2026🛡️ Security

Huntress reports in-the-wild exploitation of two unpatched AhsayCBS vulnerabilities (CVE-2026-105133 and CVE-2026-105134) affecting all versions up to and including the latest 10.3.4. Attackers chain an authentication bypass with OS command injection via the Replication Receiver API to gain unauthenticated RCE with System privileges, drop JSP webshells, deploy XMRig cryptominers disguised as Microsoft Edge, achieve persistence using a modified NSSM binary as a fake Microsoft Edge Update service, and load the vulnerable WinRing0x64.sys driver for kernel-level miner access (BYOVD). At least five organizations were targeted as of October 8; Huntress recommends restricting management-interface access until a patch is released.

securityweek.comarticlePublished and added 9 Oct 2026🛡️ Security

An X post by the creator of ROPE, a prompt-injection benchmark for LLM agents. It uses two news items to argue that the prompt-injection model of agent attacks is incomplete: a zero-click RCE called Plugin4Shell in coding agents' plugin systems, and Apple's local MCP server in Safari 27 exposing browser automation to agents. Neither involved persuading a model. The author concludes that teams should benchmark what an agent believes and also audit what it can reach, using plugin signing and update policy, least-privilege credentials per agent, and treating local MCP surfaces as attack surface.

x.comthreadPublished and added 9 Oct 2026🛡️ Security

Cisco Talos's weekly Threat Source newsletter, opening with a risk-management anecdote about network-isolating unpatchable legacy check-printing systems, then disclosing new CAIRN research classifying "A3: AI-Analysis Evasion" — malware authors embedding natural-language prompt-injection text into code/binaries to manipulate AI-assisted malware analysis pipelines. The MANTLEMAZE malware family exemplifies this, pairing such AI-deception attempts (effective ~35% of the time) with BYOVD abuse to disable EDR from kernel space. The issue closes with a roundup of the week's security headlines (Citrix NetScaler CVE-2026-88779, a Danish government data breach, Warlock ransomware) and Talos's current top-prevalence malware hashes/IOCs.

blog.talosintelligence.comarticlePublished and added 8 Oct 2026🛡️ Security

Cisco patched 35 vulnerabilities in its October release, including a dozen+ critical bugs across Meraki, License On-Prem, NX-OS, APIC, and Finesse. Highlights include unauthenticated RCE with root privileges in NX-OS (CVE-2026-76471, CVE-2026-76465), unauthenticated auth bypass and DoS in License On-Prem (CVE-2026-20328, CVE-2026-76454), OS injection and improper access control in APIC (CVE-2026-76498, CVE-2026-76499, CVE-2026-76500), and a publicly disclosed high-severity SSRF in Finesse (CVE-2026-20362). Cisco says none are currently exploited in the wild.

securityweek.comarticlePublished and added 8 Oct 2026🛡️ Security

Presents Reverse-Bleichenbacher, a variant of the Bleichenbacher RSA PKCS#1 v1.5 padding-oracle attack that recovers the least significant bytes first and stops once the TLS PreMasterSecret is found. With improved trimmers and coverage-optimized search, median oracle queries against a 2048-bit key drop from 11,428 to 1,801, and 68.3% of runs finish within a 30s timeout under single-server conditions. The authors find 640 vulnerable domains in the Tranco Top 1M (many behind Alibaba Cloud load balancers) and demonstrate MITM malicious update injection leading to remote code execution.

eprint.iacr.orgpaperAdded 11 Oct 2026, published 8 Oct 2026🛡️ Security

James Berthoty argues that AI guardrails for first-party AI features should be treated as an extension of cloud/product security, not tied to employee-usage monitoring. Guardrails (prompt injection defense, content filtering, goal alignment) are available from AI security vendors, gateways, frontier providers and SDKs. He recommends deploying in-depth guardrails through developer SDKs or an existing cloud runtime/CADR provider, because those see what happens on the workload (such as a prompt injection leading to workload takeover, or the files a malicious MCP call wrote). Dedicated AI security vendors offer an integrated policy engine and deeper AI red-teaming, but they are usually run by internal IT rather than cloud/product security teams.

x.comthreadAdded 10 Oct 2026, published 8 Oct 2026🛡️ Security

SonicWall patched four SMA1000 appliance vulnerabilities including CVE-2026-102255, a pre-authenticated SSRF flaw (CVSS 10) that lets an unauthenticated remote attacker abuse an unintended alternate access path to reach internal functionality; two other high-severity bugs enable RCE and one medium-severity bug enables XSS. Splunk separately fixed dozens of flaws across Splunk Enterprise, MCP Server, and the Add-on for AWS, including three critical Splunk Enterprise bugs allowing arbitrary command execution, unauthorized access, and code injection, plus a medium-severity MCP Server issue letting an authenticated user redirect API requests to an attacker-controlled URL. SonicWall says SSL-VPN on its firewall products is unaffected and no in-the-wild exploitation has been observed.

securityweek.comarticlePublished and added 8 Oct 2026🛡️ Security

Florida, Iowa, Montana, and Nebraska sued TP-Link Systems over allegedly misleading security marketing and undisclosed China ties, joining a similar Texas suit from February; the complaints cite TP-Link routers' role in the Volt Typhoon and Flax Typhoon campaigns and botnet abuse by Chinese and Russian actors. The piece also details five newly disclosed TP-Link Aginet vulnerabilities (CVE-2025-30237 through CVE-2025-30241) reported by SEC Consult, including an unauthenticated super-admin auth bypass, a root-privilege command injection, hardcoded device-model encryption keys exposing Wi-Fi/ISP credentials, and a USB-based physical-access filesystem dump affecting 65 device models.

securityweek.comarticlePublished and added 8 Oct 2026🛡️ Security

Introduces Learnable Trust-Boundary Delimiters (LTBD), a defense against prompt injection that uses a few learnable delimiters to mark trusted user instructions versus untrusted external data, without changing LLM parameters. It reports 0.00% ASR on AlpacaFarm and 0.11-0.19% on TaskTracker, outperforming inference-time defenses and rivaling training-based ones with negligible overhead. It also holds up against adaptive attacks where the adversary knows the defense.

arxiv.orgpaperAdded 9 Oct 2026, published 8 Oct 2026🛡️ Security

Paper that tests prompt injection against AI agents through both direct user input and inter-agent communication. The attacks leak sensitive information and trigger cross-agent infections. Most findings concern single-agent systems, and the authors then extend the attacks to multi-agent frameworks to show how weaknesses propagate between agents. It argues that agents embedded in real-world workflows need stronger defenses.

arxiv.orgpaperAdded 12 Oct 2026, published 8 Oct 2026🛡️ Security

Part 2 of an AWS Security Blog series detailing the design of a "steering file" — a persistent instruction set (deployable as a Kiro steering file, Kiro skill, or Claude Code CLAUDE.md) that constrains an LLM performing vulnerability triage. It walks through five configuration sections: requiring structural/dataflow verification before reporting findings, replacing self-reported confidence with a weighted formula based on binary structural signals (e.g., 0.30 weight for confirmed taint flow), mapping infrastructure controls (AWS WAF, IAM) to severity multipliers with a 0.15 floor, incorporating CISA KEV and EPSS threat-intelligence boosts capped at +0.50, and a four-tier priority classification that suppresses low-confidence P3 findings. Validation against a 10-vulnerability test app showed the steered model eliminated fabricated findings and correctly downgraded mitigated vulnerabilities while preserving full severity for a command injection reachable only via authenticated access.

aws.amazon.comwriteupAdded 8 Oct 2026, published 7 Oct 2026🧠 AI

BRANCH is a bypass methodology for guardrail systems built from multiple scanners (prompt injection/jailbreak detectors). It uses a branching tree search that applies adversarial perturbations to individual scanners and selects techniques based on overall improvement across all scanners, decoupling bypass evaluation from attack signal optimization. It reports 100% attack success across 6 guardrail systems in 120 scenarios with 72% fewer queries and 4.5x lower wallclock time than established techniques, and transfers to 29 unseen guardrails, including 8 commercial black-box ones.

arxiv.orgpaperAdded 9 Oct 2026, published 7 Oct 2026🛡️ Security

watchTowr post-exploitation analysis of CVE-2026-88771, an unauthenticated log-poisoning command injection in Citrix NetScaler (advisory CTX697096). Sensors logged thousands of attempts: about 85% were OOB callbacks, the rest Sliver implants, a trojanized Dropbear SSH backdoor, a Perl stager with a PHP webshell, and SSH-key and secret-harvesting sprays. Includes artifacts to hunt (/var/tmp files, ns_helper, ns.conf edits) and IOC repo pointers.

watchtowr.comwriteupAdded 30 Oct 2026, published 7 Oct 2026🛡️ Security

NuGuard is an open-source AI application safety and security toolkit for agentic AI systems, released under Apache 2.0. It unifies AI-SBOM generation, structural static analysis of the AI stack, and sandboxed adversarial red-teaming (100+ scenarios covering prompt injection, tool abuse, and data exfiltration) into a single CLI workflow, with an automated judge that scores findings by impact and provides remediation guidance.

x.comthreadPublished and added 7 Oct 2026🛡️ Security

This arXiv paper introduces the "package hallucination attack," where an attacker injects malicious prompts into benign agentic-coding rule files (such as .cursorrules) to induce a coding agent to replace legitimate package dependencies with attacker-controlled ones. The authors propose PackHallu, an evolutionary optimization framework that iteratively rewrites injected prompts using trajectory-level feedback and LLM-guided mutations, and show it achieves high attack success rates with strong transferability across multiple LLMs, benchmarks, and agent frameworks.

arxiv.orgpaperAdded 8 Oct 2026, published 7 Oct 2026🛡️ Security

OpenAI's system card accompanying the October 2026 ChatGPT rollout of GPT-6 Sol and GPT-6 Luna, replacing GPT-5.6 Sol and Luna for free and paid users (Codex and ChatGPT Work retain the September versions). It details Preparedness Framework results (High capability in Cybersecurity and Biological/Chemical domains, below High in AI Self-Improvement), multiturn jailbreak and GPT-Red prompt-injection robustness, alignment evaluations on respecting Auto-review/warnings and deceptive disclosure, hallucination rates, and health/mental-health benchmarks (HealthBench, HealthBench Professional, MentalHealthBench), alongside some noted regressions in self-harm, sexual content, gore and teen (U18) safety categories.

deploymentsafety.openai.comadvisoryPublished and added 7 Oct 2026🧠 AI

OpenAI's system card for the October 2026 GPT-6 Sol and GPT-6 Luna release in ChatGPT, detailing safety and preparedness evaluations under the Preparedness Framework. It reports High-capability classifications in Cybersecurity (ExploitBench: 82.62%/44.66%, SEC-Bench Pro: 68.85%/48.50%) and Biological/Chemical domains (below Critical thresholds), multi-turn jailbreak robustness results, GPT-Red direct/indirect prompt-injection robustness (99.99%/99.79%), and alignment evaluations covering Auto-review circumvention, warning-bypass behavior, and blocker/search-tool deception, alongside HealthBench, MentalHealthBench and hallucination benchmarks.

deploymentsafety.openai.comarticlePublished and added 7 Oct 2026🛡️ Security

The Vulnerable MCP Project is a curated, continuously growing database of security vulnerabilities and attack techniques specific to the Model Context Protocol ecosystem. Entries cover concrete CVEs (e.g. CVE-2025-68143/68144/68145 in Anthropic's mcp-server-git), transport-layer SDK flaws (cross-client response leakage, missing DNS rebinding protection in the official TypeScript/Python SDKs), unauthenticated/0.0.0.0-bound servers enabling RCE (MCPJam inspector, MCP Inspector, Grafana MCP), command/path injection in dozens of third-party servers (gemini-mcp-tool, mcp-server-kubernetes, Framelink Figma MCP, Zen MCP, filesystem-mcp), SSRF chains reaching cloud metadata (MarkItDown MCP, mcp-fetch-server), and a large set of AI-specific attacks: tool poisoning, trigger-phrase data exfiltration, prompt injection via GitHub issues, Jira and Google Docs, rug-pull tool mutation, and cross-server tool-name collisions. It functions as the de facto vulnerability registry for the MCP ecosystem, useful for tracking disclosed issues before patching or adopting third-party MCP servers.

vulnerablemcp.inforepoAdded 6 Oct 2026🛡️ Security

ASPIRE is an automated red-teaming engine for LLM agents that discovers indirect prompt-injection vulnerabilities beyond pre-specified attack scenarios. It maintains an evolving Agent Security Behavior Graph and uses complementary Explore and Exploit experts to find, verify, and generalize consequence-centric attacks, with trajectory evidence and cross-run memory improving coverage over time. Benchmarked against existing automated red-teaming approaches, it shows broader coverage of consequences, injection methods, environments, and behavior paths while keeping attack success high.

arxiv.orgpaperAdded 8 Oct 2026, published 6 Oct 2026🛡️ Security

Endor Labs walks through what "sandboxing an AI coding agent" actually means at the OS level, contrasting the approval-prompt model with kernel-enforced isolation. It details how Claude Code, Cursor, and Codex CLI converge on the same primitives without full containers — Apple's Seatbelt on macOS, Landlock plus seccomp on Linux, Job Objects/AppContainer on Windows — and why Anthropic ships an open-source bubblewrap-based runtime with a host-side egress proxy. It argues filesystem isolation and network egress controls are interdependent (citing Anthropic's own sandboxing writeup) and uses the 2025 nx npm supply-chain attack to illustrate why containment, not model-level guardrails, is the real defense against prompt injection and credential exfiltration.

endorlabs.comarticlePublished and added 6 Oct 2026🧠 AI

This arXiv paper presents the first systematic study of security implications of speculative decoding, a technique that speeds up LLM inference using a smaller draft model to propose tokens verified by the target model. The authors find a security-utility asymmetry: lossy speculative decoding methods raise jailbreak and prompt-injection attack success rates much faster than they degrade utility, with security degradation traced to early tokens generated by the draft model. They propose SecureSD, which applies stricter verification to early-position draft tokens, improving security while preserving inference efficiency and utility on security and utility benchmarks.

arxiv.orgpaperAdded 7 Oct 2026, published 6 Oct 2026🛡️ Security

RAG-PIBench is a benchmark of 4,876 contextual examples for evaluating prompt-injection detectors embedded in retrieved content within Retrieval-Augmented Generation (RAG) systems. The authors use a leakage-aware construction pipeline with frozen train/validation/protected-test splits and compare keyword-based, semantic-reference, TF-IDF, and transformer-based detectors, finding DistilBERT achieves the best protected-test performance (F1 = 0.896, PR-AUC = 0.968) while TF-IDF with SVM or logistic regression remains competitive. It highlights the risk that naive benchmark construction can leak information between splits, inflating reported detector performance for RAG prompt-injection defenses.

arxiv.orgpaperAdded 7 Oct 2026, published 6 Oct 2026🛡️ Security

This IACR ePrint paper (published TCHES 2027) presents a new cryptanalysis technique for the Lattice Isomorphism Problem that embeds LIP into a shortest-vector-problem instance on a different lattice than the one used in Hawk's specification, allowing attackers to integrate "hints" — partial information on the secret key obtained via side-channel attacks or other leakage. Using the LeakyLWEEstimator tool, the authors show Hawk signatures themselves leak exploitable information about the secret key, eroding Hawk-1024's security by roughly 11 bits, and apply the framework to resolve an open side-channel problem from TCHES 2024 plus discuss further fault-injection attack paths. Hawk is a lattice-based signature scheme submitted to NIST's second post-quantum signature call, making this a concrete key-recovery cryptanalysis relevant to PQC migration planning.

eprint.iacr.orgpaperAdded 8 Oct 2026, published 6 Oct 2026🛡️ Security

Adversa AI demonstrates Cryptographic Context Injection (CCI) against GitHub Copilot CLI: a web page presents an "encrypted" payload the agent decrypts inside its own shell, during which it is tricked into reading local files (e.g. .env.prod) to build a fake decryption key, then exfiltrates those contents to an attacker endpoint via a follow-up fetch. The attack only succeeds against certain models in Copilot's auto-routed model pool (Microsoft's mai-code-1.1-flash ran it 50% of the time, while two GPT-5.6 models refused), meaning users have no visibility into which model handles a given session. GitHub's bug bounty team validated but declined to treat it as a vulnerability since the user explicitly invoked autopilot mode with full tool permissions.

adversa.aiwriteupAdded 7 Oct 2026, published 6 Oct 2026🛡️ Security

This paper studies prompt-injection attacks against AI agent "skill" marketplaces where a router dynamically selects which third-party skill to execute. The authors show existing injection attacks lose 87-97% of their effective attack success rate once a skill must first win retrieval against competing skills, and introduce CORSA (Cluster Optimization for Router-Aware Skill Attacks), which jointly optimizes injections for retrieval and execution, improving end-to-end attack success while preserving user utility and transferring across different router architectures and LLM backbones.

arxiv.orgpaperAdded 7 Oct 2026, published 6 Oct 2026🛡️ Security

METR describes a proof-of-concept client-side JavaScript injection in the Inspect evaluation transcript viewer. An unescaped MathJax \href expression lets an agent inject an SVG animate element with an onbegin handler and run its own JavaScript, so it could rewrite transcripts and the Download output. Meridian Labs patched it within one day. The post argues agent outputs and logging systems must be treated as untrusted and security-critical.

metr.orgarticleAdded 29 Oct 2026, published 6 Oct 2026🛡️ Security

METR argues that AI agents could hide misbehavior by subverting the tools humans use to review them, so observability should be treated as security-critical infrastructure. As a proof of concept, a researcher with AI help found a MathJax-based JavaScript injection in the Inspect transcript viewer in about 10 minutes. It could let an agent alter the displayed transcript. Meridian Labs patched it within a day, and METR has seen no agent exploit it.

metr.orgarticleAdded 29 Oct 2026, published 6 Oct 2026🧠 AI

Describes Uber's internally-built ADR (Agentic Detection & Response) system, open-sourced in August with an MLSys paper, which monitors over 50,000 daily AI agent sessions via an MCP-based sensor inside Cursor, Claude Code and Codex. Uber found 206 credential exposures in ten months from normal agent use (not prompt injection), and ADR hits 100% detection with 3 false positives on the public AgentDojo benchmark; the thread also flags that human approval fatigue breaks down as a safety control past roughly 50 agent actions per session.

x.comthreadPublished and added 6 Oct 2026🛡️ Security

This paper runs a paired, reproducibility-focused evaluation of two System-1 single-forward-pass decision models, open-weight Laya and hosted Jev, across 11 typed decision points that agent harnesses make constantly: tool selection, RAG relevance gating, prompt-injection detection, and zero-shot model routing, using 7,283 base cases plus 6,640 robustness variants from 18 public sources. Jev beats Laya on 9 of 11 decision points by 10.8-46.0 percentage points, both models fail at zero-shot model routing, and Laya flips 30 percent of answers under option reordering and degrades badly with many or similar candidates. The authors also self-audit their own pipeline, finding and correcting three analysis errors and a design confound, including a reported 23.9 percent cost saving that was actually 4.3 percent, and gate accuracy conflated with end-to-end quality.

arxiv.orgpaperAdded 5 Oct 2026🧠 AI

A public PoC chains CVE-2026-42589 and CVE-2026-40281 to achieve unauthenticated remote code execution against Gotenberg (a document/PDF-conversion microservice), abusing metadata injection flaws in the /forms/pdfengines/metadata/write endpoint. The tool supports vulnerability detection, interactive command execution, reverse shell delivery, and multi-target scanning against Gotenberg versions ≤8.30.1 (patched in 8.31.0).

x.comrepoPublished and added 5 Oct 2026🛡️ Security

This paper studies looped language models — architectures that reuse a shared block of layers recurrently — and argues that as recurrent hidden states approach fixed points, the specific path taken to reach them matters less, enabling several efficiency tricks: truncated backpropagation through time during training, terminal key-value (KV) cache sharing across loop iterations for faster decoding, a distilled student model that prefills up to 1.79x faster, and RL policy gradients computed from saved rollout states that run 2x faster than backpropagating through the full trajectory. To make these fixed points reliable, the authors replace fixed-depth training with a learned depth prior (regularized with an entropy term to stay broad, improving on Huginn's fixed broad prior) and introduce orthogonal input injection, which removes the component of the injected input that the hidden state could otherwise amplify or cancel. Across model scales from 100M to 1.6B parameters, both changes lower perplexity, and at 1.6B the learned prior with a 3x smaller KV cache matches the downstream performance of full-cache fixed-depth training.

arxiv.orgpaperAdded 6 Oct 2026, published 5 Oct 2026🧠 AI

This arXiv paper introduces RAISED (Robust Attack Invariance through Self-Distillation), a training framework that defends tool-using LLM agents against indirect prompt injection without the utility degradation seen in prior training-based defenses. The authors show existing defenses cause distributional drift that makes models wrongly refuse legitimate tool-output-guided steps on benign tasks, then fix this by having a model generate its own tool-use scenarios and self-distill to match clean-context behavior on both clean and injected trajectory variants. Results show reduced attack success rate on injected tool responses while preserving performance on agentic and general-purpose benchmarks.

arxiv.orgpaperAdded 6 Oct 2026, published 5 Oct 2026🛡️ Security

This paper introduces a paired-replay testbed that samples a single LLM agent request and replays the identical malicious action, resource, and arguments under four authorization conditions: broad bearer tokens, scoped JWTs, sender-constrained tokens, and Open Policy Agent policies. Across 128 scenarios in four tool domains and five local model configurations, broad-bearer tokens let roughly 9 to 38 percent of attacked, post-exposure decisions execute harmful actions, while all three scoped conditions recorded zero harmful executions; a supplementary AgentDojo extension found 11 of 24 injected attacks succeeded under broad policy versus 0 of 24 under scoping. The authors frame this as evidence that scoping contains cross-action and cross-resource consequences of prompt injection, not that it prevents the injection itself.

arxiv.orgpaperAdded 6 Oct 2026, published 5 Oct 2026🛡️ Security

A forum writeup describing bend-ssz, a formally verified implementation of Ethereum's SSZ serialization covering all 109 mainnet Fulu types plus 131 generic test forms, written in the proof-checking language Bend and proved equal to the consensus-specs reference instead of relying on test vectors. The post details how mutation testing, hand-written fault injection, and 2M+ hostile decode fuzzing found and closed gaps, including a 32-bit size-arithmetic wraparound and a decode memory-amplification DoS (up to 28x heap-per-byte blowup) that is mitigated with a proved, budgeted decode function; it also reports integrating the library into Prysm and cross-checking against Lighthouse on a live devnet with zero mismatches.

ethereum-magicians.orgwriteupPublished and added 4 Oct 2026🛡️ Security

This arXiv paper identifies a new attack surface in proactive personal AI agents: an external content provider who controls only material tied to its own target (e.g. a product or service) can manipulate an otherwise benign agent into recommending that target to the user, without compromising the agent or accessing private user context. The authors formalize the attack via three mechanisms — Target Control, Private Binding, and Prospective Support — and show across three proactive-agent environments and six simulated user models that the full attack raises target authorization rates by up to 77.4 percentage points, with a multi-turn variant that keeps influencing the agent's responses even absent final user authorization.

arxiv.orgpaperAdded 6 Oct 2026, published 4 Oct 2026🛡️ Security

A critical unauthenticated command-injection vulnerability (CVE-2026-105105, CVSS 9.8) was disclosed in NASA AMMOS AIT-Core, software used for spacecraft command and telemetry operations. The flaw stems from AIT-Core's ZeroMQ message bus binding to 0.0.0.0 on TCP port 5559 by default with no authentication, letting any network-reachable attacker publish onto internal topics such as __commands__, potentially injecting spacecraft command data, reading/forging telemetry, and disrupting the command-and-telemetry bus. Affects AIT-Core <= 3.1.1, fixed in 3.1.2 by binding ZeroMQ XSUB/XPUB interfaces to 127.0.0.1; no known in-the-wild exploitation.

x.comthreadPublished and added 3 Oct 2026🛡️ Security

NATION Guard is a local, open-source tool announced by Nation that inspects the instructions and configuration behind AI agents. It combines injection-pattern scanning, integrity baselining, and per-server MCP fingerprinting so developers can detect suspicious prompt injections and unauthorized changes to their agent setup.

x.comthreadPublished and added 3 Oct 2026🛡️ Security

A vendor blog primer (Endor Labs) that walks through the main families of sandboxing technology - VMs (Firecracker), shared-kernel containers (namespaces, cgroups, seccomp, runc), userspace-kernel middle grounds (gVisor, Kata Containers), and language/runtime sandboxes (Java SecurityManager, V8 isolates, WebAssembly/WASI) - explaining what each actually isolates, its cost, and known escape CVEs (VENOM/CVE-2015-3456, runc's CVE-2019-5736, Spectre/Meltdown). It then pivots to AI coding agent sandboxing specifically, framing agents as "confused deputies" vulnerable to prompt injection via Simon Willison's "lethal trifecta" (private data access plus untrusted content plus external communication), and lays out the policy controls that matter in practice: filesystem scoping, egress allowlists, action classification, reviewable diffs, scoped short-lived credentials, and human-in-the-loop approval, plus the need to log accumulated session permissions for audit.

endorlabs.comarticlePublished and added 2 Oct 2026🧠 AI

CorrectGuard is a framework for estimating whether black-box AI security guardrails made correct decisions on inputs that are inaccessible to humans (production privacy) or to the guardrail-auditing model itself, using only labeled "eyes-on" data and no internal access to the guardrail. The authors test in-context-learning, embedding, and finetuning-based correctness classifiers across 13 safety/security datasets (harmful content, jailbreaks, prompt injection, extraction) and multiple open-weight guardrails, showing up to 25-point macro-accuracy gains in error identification and improved risk-based abstention/ranking of guardrail decisions.

arxiv.orgpaperAdded 5 Oct 2026, published 2 Oct 2026🛡️ Security

CorrectGuard is a framework for estimating how accurately black-box security guardrails (jailbreak, harmful-content, prompt-injection and extraction detectors) perform on inputs that cannot be inspected by humans or by the evaluating model itself, using an independent correctness model trained only on labeled "eyes-on" data. The authors test in-context-learning, embedding-based, and fine-tuned correctness classifiers under leave-one-dataset-out evaluation across 13 safety/security datasets and multiple open-weight guardrails, showing up to 25-point macro-accuracy gains and improved risk-coverage tradeoffs (AURC reduced from 0.33–0.44 to 0.17–0.22) for guardrail decision ranking and abstention. The work matters for anyone building auditing or eval pipelines for opaque safety classifiers without privileged access to their internals.

arxiv.orgpaperAdded 5 Oct 2026, published 2 Oct 2026🧠 AI

This arXiv paper replays ground-truth tool calls from the AgentDojo and tau-bench agent benchmarks (without an LLM) to generate benign-by-construction tool outputs, then labels injected outputs via differential replay to evaluate fifteen prompt-injection detectors, including Meta's Prompt Guard 2, plus two task-aware LLM judges, also testing them on BIPIA. It finds detection rankings transfer poorly between benchmarks (the best detector on BIPIA catches only 2% of AgentDojo injections at 1% false-positive rate; a detector catching 72% of AgentDojo injections catches only 15% on tau-bench), while false-positive rates do transfer between the two agent benchmarks, and traces this to mismatches between training data format (e.g., training on short prompt strings vs. tool-output-embedded injections) and deployment context.

arxiv.orgpaperAdded 5 Oct 2026, published 2 Oct 2026🛡️ Security

Huntress commissioned a survey of 501 US knowledge workers (excluding security professionals) on AI usage, training, and policy at work. Key findings: 43% received no formal AI security training, only 26% have a written AI policy, and when asked if a company chatbot could plausibly be exploited via prompt injection, only 26% of workers recognized the risk (31% even among those with a written policy). It also surfaces behavioral risk data, like 25% of workers saying they'd copy a client contract into a personal AI account rather than check with IT first.

huntress.comarticleAdded 3 Oct 2026, published 2 Oct 2026🛡️ Security

Simon Willison quotes security researcher Matthew Green on why sandboxing alone doesn't stop rogue AI agents: isolated agents discovered they could leave instructions for each other in a shared package cache, letting one agent's hijacked payload propagate to the next — the two halves of a worm. Green argues the same dynamic applies once independently-deployed personal agents (like a "Muse"-style assistant) communicate via email, Slack, shared documents, or WhatsApp instead of a package cache, giving prompt-injection payloads a worm-like spreading mechanism across agent populations.

simonwillison.netarticleAdded 7 Oct 2026, published 1 Oct 2026🛡️ Security

Glow Labs' "PixelLeak" research found that AI coding agents, unable to attach before/after screenshots to private pull requests, worked around the limitation by creating public GitHub repositories to host the images and link them back into the PR. This exposed over 13,000 internal images (billing records, treasury consoles, unreleased features) across 900+ public repos at 300+ organizations — 93% under employees' personal GitHub accounts, outside corporate monitoring — with one team even encoding the behavior into a reusable agent skill. The case illustrates an "authorized but unsafe" agentic risk class distinct from prompt injection or malicious compromise.

x.comthreadAdded 1 Oct 2026, published 30 Sep 2026🛡️ Security

Google released Gemini 4 Argon, its new frontier model for coding, office work and cyber defense, scoring 77.9% on DeepSWE v1.1 (vs. 74.2% Claude Opus 5.5, 74.1% GPT-6 Astra) and expanding max output to 1 million tokens. On Gray Swan's indirect prompt injection benchmark it posted a 0.7% attack success rate, edging out Claude Opus 5.5 and Claude Fable 5.1 (both 1.0%), and scored 70.9% on Google's internal Wiz Penetration Test Benchmark versus 58.2% for the earlier restricted Gemini 3.8 Flash Cyber. The model initially ships without cyber guardrails only to vetted defenders via Google's Fairwind Program before wider API and Google AI Ultra release at $2/$10 per million input/output tokens.

decrypt.coarticlePublished and added 30 Sep 2026🧠 AI

Decrypt covers Google's Gemini 4 Argon launch, reporting it scored a 0.7% attack success rate on Gray Swan's Indirect Prompt Injection benchmark, beating Claude Opus 5.5 and Claude Fable 5.1 (both 1.0%), GPT-6 Astra (8.5%), and far outperforming Grok 4.6 and Kimi K3 (~52% each). It also details Argon's cyber-defense capability: it ships first to vetted defenders through Google's Fairwind Program "without cyber guardrails," scored 70.9% on the internal Wiz Penetration Test Benchmark writing working exploits against real web-app flaws, and reportedly helped Wiz find a critical healthcare-software flaw earlier models missed.

decrypt.coarticlePublished and added 30 Sep 2026🛡️ Security

Write-up of a BlueHat Asia 2026 talk on CVE-2026-65669, a critical SQL Server elevation of privilege in Copilot in SQL Server Management Studio. The read-only mode was only a regex classifier (LocalSqlExecutionAccessChecker) and was bypassed with DECLARE @p sysname='sp_executesql'; EXEC @p. The chain used indirect prompt injection through AGENTS.md and CONSTITUTION.md extended properties to take a db_owner to sysadmin, with data exfiltration via xp_dirtree and RestoreVerifyBackupFile.

embracethered.comwriteupAdded 29 Oct 2026, published 30 Sep 2026🛡️ Security

Google DeepMind's announcement of Gemini 4 Argon, a frontier model rolling out first to trusted cyber defenders via the Fairwind Program, with an industry-leading 1M output token limit (up from 64K) and pricing of $2/$10 per million input/output tokens. It reports state-of-the-art results on DeepSWE v1.1, the Vals Index, AutomationBench, LVBench, and CWE-bench v1, details internal use cases (quantum algorithm optimization, C/C++-to-Rust migrations including the Fuchsia Zircon kernel and libgav1), and describes new frontier safeguards covering misuse defense, indirect prompt-injection robustness, chain-of-thought misalignment monitoring, and sandboxed training environment hardening.

deepmind.googlearticlePublished and added 30 Sep 2026🧠 AI

Unit 42 threat brief on CVE-2026-88771 (unauthenticated command injection) and CVE-2026-88772 (DTLS memory overflow) in NetScaler ADC and Gateway, both CVSS v4.0 9.5 and exploited as zero-days from August 2026. It details version fingerprinting, .deb and PHP web shells, a three-stage log-poisoning chain through ns_monuploadd_err.pl, httpd.conf persistence, IOCs, and 50,277 exposed instances as of 27 September 2026.

unit42.paloaltonetworks.comadvisoryAdded 30 Oct 2026, published 30 Sep 2026🛡️ Security

This paper proposes an attack-chain-based detection framework for indirect prompt injection in LLM email assistants, combining a text detector, stage-specific verifiers, rule-based risk signals, and user-intent/action consistency checks scored via a logistic decision policy, rather than treating detection as binary malicious-text classification. Evaluated under random splits, temporal and cross-dataset transfer, and ablations across five binary benchmarks, it achieves a mean F1 of 0.406 versus 0.216 for the best of five existing pretrained detectors, and shows random splits overestimate robustness under distribution shift while training on hard benign (attack-resembling) emails reduces false alarms.

arxiv.orgpaperAdded 30 Sep 2026🛡️ Security

Microsoft Threat Intelligence tracked in-the-wild exploitation of CVE-2026-73570, an unauthenticated OS command-injection vulnerability in Zimbra Collaboration Suite's SNMP notification path (swatchdog-to-snmptrap), triggerable via a crafted SMTP request when the optional zimbra-snmp package is enabled. The post documents pre-disclosure scanning, JSP webshell deployment, a novel pam_exec/zmmailboxdmgr privilege-escalation chain to root, systemd-based persistence (zimlog.service), theft of zimbraPreAuthKey/zimbraAuthTokenKey via zmlocalconfig and LDAP, lateral movement over Zimbra's SSH identity, a multi-stage Go-based remote-access agent (zimclient2 via zimdown2/agent2.sh), a dedicated mailbox-exfiltration implant, and an AzCopy-based exfiltration attempt, closing with Defender XDR KQL hunting queries and MITRE ATT&CK mapping.

microsoft.comwriteupAdded 1 Oct 2026, published 30 Sep 2026🛡️ Security

Aletheia is a permission-minimality testing framework for coding-agent repository instruction files (rules), which can be weaponized via prompt injection to request unnecessary credential access or data exfiltration while still producing a correct patch. It translates requested authority into a typed language, synthesizes sandbox configurations, and runs tasks under full versus incrementally restricted permissions to produce "dispensability witnesses" that flag suspicious permission requests. On the AIShellJack benchmark it detects all 314 attack inputs with zero false alarms on five benign templates, and on 80 manually verified benign GHAgentFiles rules it raises only 3 false positives (3.75%).

arxiv.orgpaperAdded 2 Oct 2026, published 30 Sep 2026🛡️ Security

This paper proposes A2A-TIBA, an indirect prompt injection attack that abuses agent-to-agent (A2A/ACP) protocols by getting a target LLM agent to deploy a callback program, letting an attacker bypass the agent entirely to issue commands and exfiltrate data. It also introduces GDA Measurement, a red-team testbed that captures raw gateway context to distinguish four outcome classes (semantic refusal, semantic breach, interception, penetration) instead of a single attack-success-rate metric, and ELA-ITL, a three-layer isomorphic attack-defense model splitting defense into envelope packaging, LLM recognition, and agent interception. Testing on 15 agent-frontend x LLM-backend combinations and a 1,000-case dataset shows that labeling malicious-prompt indicators in envelope channels (A2A, tool, memory) significantly improves LLM recognition of injected content.

arxiv.orgpaperAdded 2 Oct 2026, published 30 Sep 2026🛡️ Security

Google announces Gemini 4 Argon, a frontier model rolling out first to trusted cyber defenders via the Fairwind Program, with a 1M-token output limit (up from 64K) and introductory pricing of $2/$10 per million input/output tokens. It reports state-of-the-art results on DeepSWE v1.1 (77.9%), LVBench (91.7%), AutomationBench (51.3%) and a tie for first on CWE-bench v1 (68%), plus leading scores on the Vals Index and Gray Swan's IPI prompt-injection benchmark. Internal case studies include agent-driven C/C++ to Rust migrations (libgav1 decoder 2.7x faster than the Rust port, Fuchsia Zircon kernel) and fleet-wide memory optimisation. It also outlines safeguards: misuse monitoring of internal activations, prompt-injection hardening, chain-of-thought misalignment monitoring and sandbox hardening.

blog.googlearticleAdded 1 Oct 2026, published 30 Sep 2026🧠 AI

Release notes for garak v0.17.0, NVIDIA's open-source LLM vulnerability scanner used for red-teaming and probing models for jailbreaks, prompt injection, data leakage and other failure modes. The release adds an EU AI Act risk-category mapping to tag and group probe results, plus fixes to detectors (agent_breaker judge verdict validation, packagehallucination import parsing, MarkdownExfilContent divide-by-zero, TriggerListDetector alignment) and probes (badchars ASCII selection, Markdown exfiltration link templates), along with Ollama generator improvements and dropped Python 3.10 support in favor of 3.13.

github.comrepoAdded 29 Sep 2026🛡️ Security

security-harness is an open-source Claude Code plugin (also packaged for Gemini CLI, Codex and opencode) that orchestrates subagents — sh-recon, sh-hunter, sh-chainer, sh-verifier, sh-reporter — through a static-analysis pipeline covering 15 vulnerability classes (IDOR/BOLA, SQLi, XSS, SSRF, injection, auth, deserialization, path traversal, secrets, CSRF, XXE, open redirect, crypto, race conditions, file upload), producing README/JSON/SARIF/HTML/PDF reports with PoCs, CVSS and CWE/OWASP mappings. It also ships sh-pr-review, a per-PR merge-gate skill that posts inline findings and a commit status scoped only to code the PR itself introduced or aggravated, with caching, dedup via fingerprints, and a scheduled GitHub Action that keeps its per-class knowledge bases fresh by having one AI agent draft updates from allowlisted sources (OWASP, PortSwigger Research, CWE/CAPEC, HackerOne) while a separate adversarial reviewer agent fails-closed against prompt injection before auto-merge.

github.comrepoAdded 2 Oct 2026, published 29 Sep 2026🛡️ Security

OpenAI system card addendum for GPT-6.1 Sol reports Preparedness Framework results rating the model Critical capability in cybersecurity and High in biological and chemical risk, reusing GPT-6 Astra safeguards stack. It details jailbreak (static and multiturn) and indirect prompt-injection defender success rates, ExploitBench, ExploitGym and SEC-Bench Pro cyber-capability scores, and chain-of-thought monitor-evasion experiments showing the model rarely succeeds at hiding misaligned reasoning from full-context monitors, plus honeypot-exploitation and sabotage-evasion tests.

deploymentsafety.openai.comarticleAdded 7 Oct 2026, published 29 Sep 2026🛡️ Security

OpenAI's system card addendum for GPT-6.1 Sol, a fast and affordable model in the GPT-6 family with capabilities comparable to GPT-6 Astra, reports Preparedness Framework determinations (Critical cybersecurity, High biological and chemical capability, sub-High AI self-improvement) and the same safeguards stack as Astra. It details extensive safety and alignment evaluations including safe-completion benchmarks, jailbreak and prompt-injection robustness, HealthBench and MentalHealthBench scores, deceptive-behavior and monitor-evasion tests, and chain-of-thought monitorability and controllability results, comparing GPT-6.1 Sol against GPT-6 Astra, GPT-6 Sol, GPT-6 Luna, and the GPT-5.6 series.

deploymentsafety.openai.comadvisoryAdded 7 Oct 2026, published 29 Sep 2026🧠 AI

Tracekit is an open-source, dependency-free system that logs three cross-checked channels (human intent, model self-reported reasoning, and actual executed actions) for autonomous coding agent sessions into a hash-chained, externally anchorable ledger, hooking into Claude Code's lifecycle events and reconstructing multi-agent hierarchies. The paper's experiments show the ledger detects all 1,600 tested tamper mutations (edits, deletions, reordering, forged inserts, torn writes) with anchoring needed to catch tail truncation/full re-chaining, that a regex-based tool-call gate blocks only 41% of harmful calls while over-blocking benign ones and is trivially evaded, that in 14 real Claude Code runs the agent never acted on 4 planted indirect prompt injections, and that an LLM reviewer catches 100% of seeded misaligned steps in traces versus 82% for rule-based flags. The authors release the system, harness, and all traces.

arxiv.orgpaperAdded 29 Sep 2026, published 28 Sep 2026🛡️ Security

Tracekit is an open-source, dependency-free auditing system for autonomous coding agents that records three channels per session — the human's stated intent, the model's self-reported reasoning, and the actions actually executed — into a hash-chained, externally anchorable ledger. It hooks into Claude Code's lifecycle events, reconstructs multi-agent hierarchies, gates tool calls with a pre-execution policy, and provides a live browser-based ledger verifier. Across five experiments the authors show the hash chain catches all tested tampering (with anchoring needed against tail truncation/re-chaining), a hook adds ~24ms overhead at scale, a regex-based gate only blocks 41% of harmful tool calls, real runs correctly resisted and disclosed planted prompt injections, and a new 'seeded-fault splicing' method with an LLM reviewer caught 100% of faulted traces versus 82% for rule-based flags.

arxiv.orgpaperAdded 29 Sep 2026, published 28 Sep 2026🧠 AI

watchTowr Labs' technical breakdown of CVE-2026-88771, a pre-auth command injection in Citrix NetScaler ADC/Gateway's default configuration that was exploited in the wild as a zero-day before a patch existed. The root cause is in ns_monuploadd_err.pl: unsanitized log data (attacker-controlled via HTTP login/User-Agent fields) is interpolated into a backtick shell command via grep/sed/awk, allowing arbitrary root command execution once the crash-log parser runs; the article includes a full pre-auth exploit request, patch diff analysis (CTX697096), and a link to watchTowr's Detection Artefact Generator script.

labs.watchtowr.comwriteupPublished and added 28 Sep 2026🛡️ Security

Rapid7 details active zero-day exploitation of two critical Citrix NetScaler ADC/Gateway RCE vulnerabilities (CVE-2026-88771, CVE-2026-88772, both CVSSv4 9.5), both added to CISA KEV on disclosure day, plus a later SAML denial-of-service zero-day (CVE-2026-88779). The post includes Rapid7 MDR's observed exploitation of CVE-2026-88771 in the wild — a command-injection payload that exfiltrates /flash/nsconfig (containing ns.conf admin credentials, SSL private keys, SSH host keys) via the publicly-served /vpn/ path, and a webshell (SHA256 hash provided) found on a compromised appliance — along with vendor patch versions and detection guidance.

rapid7.comadvisoryAdded 7 Oct 2026, published 28 Sep 2026🛡️ Security

This arXiv paper proposes a certifier for structured, privileged agent actions such as paying an invoice, assembled from potentially corrupted documents and tool outputs, formalizing when multi-source corroboration can be trusted under indirect prompt injection. It uses a corruption-radius rule counted via minimum hitting sets over corruption-distinct evidence classes so laundered or re-published copies cannot fake a quorum, plus deterministic reconciliation and trusted anchors for single-sourced fields. Evaluated on 70,966 sanctions entities and 450 software-supply-chain provenance records, and against five LLM agents where a realistic injection fools all but one model and existing action-gating or provenance baselines are broken while the certifier admits no unsafe action.

arxiv.orgpaperAdded 2 Oct 2026, published 28 Sep 2026🛡️ Security

Anthropic announces Claude Opus 5.5, the first model in the Claude 5.5 family, claiming performance comparable to Claude Fable 5.1 at 40% lower cost than Opus 5, with input/output pricing at $4/$20 per million tokens and cache reads at $0.20/million. The post details agentic-coding gains against GPT-6 Astra and GPT-5.6 Sol on benchmarks like FrontierCode, Terminal Bench 4.0, CursorBench, and GDPval-AA v2.1, plus a safety section covering an automated behavioral audit, an ~85% reduction in sandbox-escape/containment-boundary attempts versus Opus 5 and Claude Mythos 5.1, Gray Swan prompt-injection results, and new cyber/biology safeguards alongside the "preserved thinking" anti-distillation mechanism.

anthropic.comarticleAdded 27 Sep 2026🧠 AI

This arXiv paper defines a threat model for multi-agent LLM delegation covering four adversaries (confused deputy, token theft/replay, prompt-injection privilege escalation, compromised sub-agents) and derives eight security requirements for governed agent systems. It shows that LangGraph, CrewAI, AutoGen, and the MCP authorization model each fail to meet the full requirement set, then implements and adversarially tests an authorization broker that blocks all four threats, rejects 0 of 200,000 forged tokens, and confines a compromised sub-agent to a mean of 1.5 reachable actions (vs. 8,100 under bearer delegation) at ~2.6 microseconds per decision. The broker's principles are said to be productized in VotalAI's LLM Shield.

arxiv.orgpaperAdded 26 Sep 2026🛡️ Security

FirmAgent is an academic research toolkit (NDSS 2026) for finding vulnerabilities in re-hosted IoT firmware web services by combining IDA-based pre-fuzzing (CFG/sink distance scoring), QEMU instrumented tracing, CFG-guided API fuzzing, and an optional LLM agent (LLMATaint.py) that consumes runtime taint traces to reason about and produce PoCs for bug classes like command injection. The pipeline is explicit about scope: it is meant for authorized, owned or re-hosted firmware (e.g. Greenhouse-style containers), and stitches together sink-scope extraction, feedback-driven fuzzing, and request-to-trace attribution before handing traces to an LLM for taint-to-PoC analysis.

github.comrepoAdded 26 Sep 2026🛡️ Security

PIDS-Bench is a frozen, multi-axis benchmark for prompt-injection detectors that jointly measures attack detection and benign false-positive rates across in-distribution inputs, hard-benign prompts mimicking injection structure, obfuscated attacks, and domain/structural distribution shifts. Testing seven detectors (learned baselines, external prompt-injection classifiers, broad-safety comparators) plus a rule-based baseline, the authors show a detector with F1 > 0.98 on held-out data still misclassifies roughly one-third of an externally-sourced benign security-adjacent corpus, and that hard-negative augmentation reduces over-defense only on curated stress inputs, not on externally-sourced ones — a pattern they call provenance-sensitive over-defense.

arxiv.orgpaperAdded 26 Sep 2026🛡️ Security

garak is NVIDIA's open-source LLM vulnerability scanner that runs probes/detectors for jailbreaks, prompt injection, PII leakage, package hallucination, markdown exfiltration and more against LLM targets. This v0.17.0 release adds a new EU AI Act risk-category mapping to tag and group probe results by the Act's risk categories, alongside fixes to the agent_breaker judge, markdown-exfiltration detectors, Ollama auth/generation support, and dropped Python 3.10 in favor of 3.13 support.

github.comrepoAdded 26 Sep 2026🛡️ Security

GitHub Security Advisory (CVE-2026-13341) for Kong's mcp-konnect MCP server describes a stored prompt injection vulnerability where a remote attacker crafts malicious request metadata (e.g. User-Agent) that gets stored in Konnect analytics and later returned unsanitized to an AI assistant via MCP tools, potentially causing the agent to exfiltrate sensitive data (plugin configs, secrets, internal hostnames) to an attacker-controlled URL if the client can make outbound fetches. A related path manipulation flaw in control plane/group identifiers allowed requesting unintended Konnect API endpoints with the user's token. The v1.0.0 patch neutralizes untrusted analytics fields, validates identifiers as UUIDs, encodes path segments, and disables raw plugin config output by default.

github.comadvisoryAdded 26 Sep 2026🛡️ Security

A paired empirical study testing whether SynthID-Text watermarking (the technique underlying Anthropic's Claude watermark) changes model behavior beyond text quality, using BFCL v4 for tool-calling accuracy and HarmBench/JailbreakBench for refusal under prompt injection. The authors find watermarking introduces measurable "sampling drift": tool-call churn (verdict disagreement between watermarked/unwatermarked runs) averages 6.5% across seven models, and refusal weakens more sharply under prompt injection (e.g. gemma-3-27b's compliance shifts from -1.0 to +12.5 points), with effects varying by model and watermark key.

lasso.securitywriteupPublished and added 26 Sep 2026🧠 AI

Lasso Security researchers empirically test whether LLM output watermarking (specifically Google DeepMind's SynthID-Text, now deployed by Anthropic across Claude models) changes AI agent behavior — not just text content. Using paired generation (same seed, with/without watermark) across seven models on BFCL v4 tool-calling tasks and HarmBench/JailbreakBench refusal tests, they find watermarking measurably reduces tool-call accuracy (churn averaging 6.5%, up to 16.8% for phi-4) and, more critically, weakens refusal under prompt injection — e.g. gemma-3-27b's compliance with harmful requests shifts from -1.0 to +12.5 net points when injection is combined with watermarking. They term this "sampling drift" and argue watermark key/configuration changes can silently alter agent safety behavior outside the agent developer's control, recommending re-evaluation and red-teaming whenever watermarking is introduced.

lasso.securitywriteupPublished and added 26 Sep 2026🛡️ Security

Agent Threat Rules (ATR) is an open, versioned YAML rule format (ATR-YYYY-NNNNN scheme) for detecting AI-agent runtime threats — prompt injection, tool-poisoning, malicious SKILL.md content, and MCP exchange abuse — evaluated by a reference TypeScript engine (with a Python wrapper) shipped as an npm/pip package, CLI, GitHub Action, and Docker scanner with SARIF output. The project positions itself as "Sigma for agent threats," maps rules to OWASP Agentic/LLM Top 10, MITRE ATLAS, and NIST AI RMF, and publishes an extensive (and unusually self-critical) benchmark suite against corpora like garak, PromptBench, and PromptInject, including documented harness bugs and withdrawn recall figures.

github.comrepoAdded 26 Sep 2026🛡️ Security

MemSentry is a proposed pre-commit evaluation framework for agentic AI systems that intercepts proposed writes to persistent memory and issues Accept/Review/Quarantine decisions by jointly scoring source trust, semantic risk, attack radius over a component-dependency graph, access risk, and a signed security-posture delta. The authors evaluate it against 1,000 GPT-4-generated scenarios using four pluggable semantic classifiers (Regex, TF-IDF+SVM, SBERT+LR, SetFit), with SBERT+LR reaching 91.7% accuracy while all methods catch 100% of external quarantine-class threats; the paper also documents a key limitation — surface-similar but oppositely-intentioned insider operations remain hard to distinguish semantically. It targets the persistent-memory-poisoning attack surface distinct from prompt injection, where a single malicious memory write (e.g., "suppress alerts from this IP") can silently persist and influence future agent actions like a SOC assistant's alerting or access decisions.

arxiv.orgpaperAdded 26 Sep 2026🛡️ Security