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bleepingcomputer.comarticle🛡️ Security

Hugging Face malware campaign returns to hijack GPUs for crypto mining

A campaign of 31 malicious Hugging Face repositories across seven accounts, found by Pluto Security, posed as small Qwen2 checkpoints and used trust_remote_code to run a cryptominer and reverse shell on GPU inference hosts. The top model reached 28,412 downloads and scanned clean, and a second wave returned within days of takedown. The article also covers a fake Solana starter kit on GitHub that installs NetSupport Manager via a PowerShell one-liner aimed at AI coding agents.

Hugging FaceQwenXinference+3
Pluto SecurityAir Securitytrust_remote_code+9

Supply Chain, AI Security, Threat Intel· Added 30 Oct 2026, published 29 Oct 2026

oversecured.comwriteup🛡️ Security

Introducing MavenGate: a supply chain attack method for Java and Android applications | Oversecured Blog

MavenGate is Oversecured's research on hijacking Maven dependencies by buying expired domains behind groupIds on Maven Central and JitPack. It found 6,170 of 33,938 checked domains (18.18%) vulnerable, and tested the attack with its own com.oversecured:hello-world library. It lists defenses (Gradle verification-metadata.xml, PGP signatures) and proposes changes to repository signing.

MavenGradleMaven Central+3
MavenGateOversecuredSonatype+2

Supply Chain, Mobile Security, AppSec· Added 29 Oct 2026

microsoft.comarticle🛡️ Security

Tracking AI adoption in North Korean threat actor tradecraft

Microsoft Threat Intelligence report on how North Korean actors use AI, ranking Jade Sleet, Coral Sleet and Jasper Sleet as operationalized, Diamond Sleet, Onyx Sleet, Pearl Sleet and Sapphire Sleet as accelerating, and Emerald Sleet as expanding. It documents AI-generated lures (100+ Onyx Sleet PDFs, August and September 2026), AI-built tooling such as Coral Sleet's private GitHub repository trojanizing, and Onyx Sleet and Pearl Sleet use of the ARTEX agentic pentest framework. It ends with mitigation and Defender guidance.

CursorGitHubRust+2
Jade SleetOnyx SleetCoral Sleet+9

Threat Intel, AI Security· Published and added 29 Oct 2026

x.comthread🧠 AI

Laban (@lunkertw) on X

An X post summarising five AI items: Google DeepMind's Gemini 4 Carbon (88.2% SEC-bench Pro, 54.8% ExploitGym, 71.0% CWE-bench, 59 on Artificial Analysis Intelligence Index v5.0), Ed Zitron's critique of Anthropic's S-1, a Utah Claude Code pilot, and the repos beenuar/AiSOC and expo/skills. In the Utah pilot, 34 developers in 10 agencies took part over four weeks, 80% had a working setup within 30 minutes, and 71% saved over 20 hours. It gives short summaries and links, not primary analysis.

Claude CodeModel Context ProtocolPython+6
Google DeepMindGemini 4 CarbonSEC-bench Pro+9

models, coding-agents, ai-policy· Added 29 Oct 2026, published 28 Oct 2026

simonwillison.netarticle🧠 AI

GitHub Octoverse 2026

Simon Willison's link post on GitHub Octoverse 2026, announced by GitHub EVP Jay Parikh at GitHub Universe on 28 October 2026. Merged pull requests tripled in under a year to 220 million per month, commits passed 7.38 billion per month, and new repositories doubled to 30.3 million per month. It quotes the methodology for country, industry (NAICS) and "interoperability or reverse engineering" repository counts. The post does not analyse the report beyond these figures.

GitHub
Simon WillisonJay ParikhOctoverse

ai-policy, coding-agents· Published and added 28 Oct 2026

endorlabs.comarticle🛡️ Security

How to evaluate ADLC security solutions: A buyer's checklist | Endor Labs

Buyer's checklist from Endor Labs for evaluating security tools in the agentic development lifecycle (ADLC), where AI coding agents write code and take actions such as package installs, CI edits and tool calls. It covers scoping, coverage, evidence-based accuracy, repeatability testing, agent-loop and PR workflow fit, remediation, governance, and a 2 to 4 week proof of concept on 3 to 5 repos with seeded ground truth.

Endor LabsAURIModel Context Protocol+3
ADLCIDORNIST SSDF+1

AppSec, AI Security, DevSecOps· Published and added 28 Oct 2026

arxiv.orgpaper🧠 AI

FeatureArc: Benchmarking Coding Agents on Evolving Features

FeatureArc is a benchmark for coding agents on evolving features, built by a pipeline that mines repository histories into multi-stage tasks across four programming languages. It has 73 manually reviewed tasks of 2 to 10 stages, validated with fail-to-pass and pass-to-pass tests. Across 10 agents, pooled success drops from 62.7% at the first stage to 28.5% for the whole feature. Inherited defects appear in 72.9% of failed later stages.

LLM
FeatureArcTencentHunyuan+1

evals, coding-agents, research· Added 28 Oct 2026, published 27 Oct 2026

wiz.ioarticle🛡️ Security

The Pwn Request Reckoning: What Still Works Against GitHub Actions

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.

GitHub ActionsGitHubzizmor+1
pwn requestscript injectionartifact poisoning+2

DevSecOps, AppSec· Published and added 26 Oct 2026

x.comthread🛡️ Security

alex lee (@alexlee20122022) on X

Gheist is a GitHub campaign disclosed by Wiz in October 2026. Stolen tokens push ci-sync-XXXXXX branches with a sync-check workflow that dumps repo secrets base32-encoded to evade log masking, fetches the logs via API, then deletes the run. 13,500+ branches and 850+ accounts were hit since 15 September. Public repos are protected by the approval hold; private and Enterprise repos are not. The thread lists IOCs (.gdmp_pat files, "gheist" user agent, "ci: sync config" commits) and rotation steps.

GitHub ActionsGitHubWiz+2
Gheistci-sync branchsync-check.yml+3

DevSecOps, Threat Intel, Supply Chain· Added 26 Oct 2026, published 25 Oct 2026

x.comtool🧠 AI

Dan Kornas (@DanKornas) on X

jshook is an open-source (AGPL-3.0) MCP server that gives AI agents a search-first, profile-aware reverse-engineering workspace for JavaScript, browser traffic, WASM and native processes. Agents start with a small searchable tool surface and move to workflow or full profiles only when needed. It drives Chromium or Camoufox over CDP, captures WebSocket traffic, has HTTP, GraphQL and Burp Suite helpers, and supports hot-reload plugins and declarative workflows. The post is a short announcement; the repository link is in a reply.

Model Context ProtocolJavaScriptWebAssembly+6
jshookDan Kornas

mcp, agents· Added 28 Oct 2026, published 25 Oct 2026

wiz.iowriteup🛡️ Security

Gheist: Attempted Scaled Abuse of Stolen GitHub Tokens Stumbles

Gheist is a campaign tracked by Wiz Research since 15 September 2026 that uses stolen GitHub tokens to push a sync-check workflow on ci-sync-* branches in every reachable repository. The workflow prints base32-encoded secrets into logs, which the tool downloads through the GitHub API and then deletes. Over 13,500 branches from 850+ accounts were recovered. The post covers the two tool variants, a buggy self-hosted runner payload, GitHub's approval hold (which does not cover private repositories), overlaps with other campaigns, hunting queries, IOCs and hardening steps.

GitHubGitHub ActionsAWS+3
GheistGhostActionPolinRider+6

Threat Intel, DevSecOps, Blue Team & Detection· Published and added 25 Oct 2026

socket.devwriteup🛡️ Security

New Evidence Shows LiteLLM Secret-Stealing Workflows Ran 11 Days Before Supply Chain Attack

Socket's Threat Research team reports that malicious cache.yml workflows ran in the BerriAI/litellm repository on 10 and 12 October 2026, eleven days before the 21 October release attack that published litellm==1.107.0. Each commit pushed to a short-lived ci-tmp-<hex> branch, then deleted it, sending base64-encoded CI secrets to webhook.site. Evidence comes from Actions metrics and environment deployment records; 20 secret names were exposed.

LiteLLMGitHub ActionsGitHub+3
ci-tmp branchescache.ymllitellm==1.107.0+6

Supply Chain, DevSecOps, Blue Team & Detection· Published and added 23 Oct 2026

x.comthread🧠 AI

Big Bull (@BIGBULLapp) on X

A post by BIGBULLapp on X about a TensorBlock GitHub index of Model Context Protocol servers, described as a TypeScript list so agents call tools someone has already wired up. It cites 1470 forks, 943 stars and 15 open issues. The author notes that curated lists go stale when a server changes its schema. The repository name is truncated in the post.

Model Context ProtocolGitHubTypeScript
TensorBlock

mcp· Added 24 Oct 2026, published 23 Oct 2026

arxiv.orgpaper🧠 AI

Tool-Calling LLM Agents Under Realistic MCP Faults: Scale Does Not Purchase Fault Tolerance

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.

Model Context ProtocolOpenAI Agents SDKLangChain+2
MCP-Injectorgpt-oss-120bOpenAI

mcp, evals, agents, research· Added 26 Oct 2026, published 23 Oct 2026

securityweek.comarticle🛡️ Security

LiteLLM Compromised in Fresh Supply Chain Attack

LiteLLM version 1.107.0 was published with malware to PyPI and Docker Hub on October 21, for about three hours and roughly 49,000 downloads. Attackers used GitHub CLI OAuth tokens, likely leaked through Claude Code into LiteLLM logs, to disable branch protections, redirect the releaser to a lookalike repository and sign poisoned artifacts. The payload is an infostealer and RAT; Wiz saw Amazon Bedrock abuse. The last clean version is 1.106.2.

LiteLLMPyPIDocker+3
Berri-AI/litellmLLMjackingdead drop+1

Supply Chain, DevSecOps, AI Security· Published and added 23 Oct 2026

huggingface.copaper🧠 AI

Cache Engineering for Agents (AKV)

AKV introduces cache engineering, which lets LLM agents control their active KV cache with drop (exclude cache from future attention) and repos (adjust retained keys' position encodings) without editing the trajectory or re-prefilling. The AKV serving engine keeps a stateless API while managing stateful cache reuse, eviction and restoration. A tool-response rolling-drop policy raised benchmark scores by 1.7 points and cut cost 27.7% versus threshold-triggered summarization.

LLMTransformerGitHub+1
AKV

inference, agents, research· Added 23 Oct 2026

x.comthread🛡️ Security

Dark Web Intelligence (@DailyDarkWeb) on X

LiteLLM suspects its October 21 release compromise began with Claude Code responses containing GitHub CLI OAuth tokens that were written to logs of an internet-facing internal LiteLLM gateway. Attackers allegedly stole those tokens, used an organization-owner token to disable branch protections, and pushed poisoned artifacts from a lookalike repository. How they entered the gateway is unconfirmed, and this is not a proven Claude Code vulnerability.

LiteLLMClaude CodeGitHub+1
LiteLLM release compromiselookalike repositorybranch protection bypass

Supply Chain, DevSecOps, AI Security· Added 25 Oct 2026, published 22 Oct 2026

eliastaylor.comarticle🧠 AI

There isn't an easy exploit for this PHP vulnerability

An opinion post from 21 October 2026 arguing that a widely feared PHP vulnerability has no easy exploit. The author says the many GitHub "PoC" repositories fail against a vanilla PHP instance in Docker. They claim LLM agents produced them by depending on a local-file-inclusion flaw or by modifying the server to be vulnerable. The author also argues that LLM defaults make many people's judgements identical.

PHPDockerGitHub+2
CVE-2026-109618CVE-2026-109619GPT+3

coding-agents· Added 22 Oct 2026, published 21 Oct 2026

wiz.iowriteup🛡️ Security

LiteLLM Compromised, Steals Credentials

LiteLLM version 1.107.0 was uploaded to PyPI on 21 October 2026 with a credential stealer, and the same build reached GHCR and Docker Hub images. Wiz describes the three dropped files (cook.pth, cook.py, sitecustomize.py), exfiltration to a fake litellm.dev domain, a GitHub dead drop for a second stage, and the malicious commits pushed through the lookalike Berri-AI repository. The last safe version is 1.106.2.

LiteLLMPyPIDocker+3
Berri-AIcook.pthsitecustomize.py+2

Supply Chain, Threat Intel, AI Security· Published and added 21 Oct 2026

socket.devwriteup🛡️ Security

LiteLLM PyPI Package and Docker Images Compromised to Steal Cloud and AI Credentials

LiteLLM 1.107.0 on PyPI and GHCR images shipped Python startup hooks (cook.pth, sitecustomize.py) that steal cloud, SSH, browser and AI-tool credentials, including LiteLLM proxy database credentials. Image build provenance recorded a lookalike Berri-AI/litellm source repository. The post decodes the payload, encrypted exfiltration and GitHub-driven remote loader, and lists containment steps, MITRE ATT&CK mappings and IOCs.

LiteLLMPyPIPython+3
Berri-AIprivcollectcook.pth+12

Supply Chain, Malware & RE, Threat Intel· Published and added 21 Oct 2026

github.comrepo🛡️ Security

eness/php2shell-CVE-2026-109618-CVE-2026-109619-PoC

php2shell is the name given to two critical pre-auth remote code execution flaws, CVE-2026-109618 and CVE-2026-109619, in PHP core's session upload progress handler (php_session_rfc1867_callback), where zend_hash_update frees live zval pointers that are later reclaimed and redirected into zend_call_function to run zif_system. This repository ships poc_109618.py, a fully automated four-stage HTTP exploit that leaks ASLR offsets via Set-Cookie headers against php:8.4.26-apache on Debian Bookworm, along with a root-cause C source patch, mitigation scripts to disable session.upload_progress, and WAF/ModSecurity/Lighttpd/Apache rules plus detection guidance for anomalous PHP worker child processes. Confirmed PHP versions include 8.4.4 and 8.2.34, with EOL branches (5.x, 7.x, 8.0, 8.1) left without official vendor patches.

PHPDockerCloudflare+1
CVE-2026-109618CVE-2026-109619PHP2Shell+6

Offensive Security, AppSec, Blue Team & Detection· Added 23 Oct 2026, published 21 Oct 2026

github.comrepo🛡️ Security

ikow/php2shell-poc

php2shell-poc is a proof-of-concept and detection toolkit for CVE-2026-109618 and CVE-2026-109619, two PHP vulnerabilities tied to session.upload_progress handling and a Zend engine out-of-memory bailout path affecting PHP 5.4.0 through 8.5.11. The repository includes three working exploit chains, a Docker-based lab (PHP-FPM, nginx, Apache mod_php) for reproduction, and pre-built Suricata, Sigma, ModSecurity, and Lua detection rules. The author recommends disabling session.upload_progress as an interim mitigation, noting the underlying memory corruption requires a full PHP patch to fix.

PHPWordPressDocker+3
CVE-2026-109618CVE-2026-109619GHSA-w8hw-w9fx-j79w+3

AppSec, Offensive Security, Blue Team & Detection· Added 23 Oct 2026, published 21 Oct 2026

opensourcemalware.comtalk🛡️ Security

The OpenSourceMalware Show #26

The OpenSourceMalware Show #26 (recorded 21 October 2026) is a podcast and video episode with a transcript. Topics: GlassWorm's compromise of four OVH CLI versions through a contributor account stolen about seven months earlier, malware split into "compound payloads" across packages (including the webrunc PyPI package and DPRK's private .npmrc registry trick), and GhostAction planting a PolinRider-style fake font stealer in repos. Also covers commit signing and LLM-assisted threat actors.

npmPyPIVS Code+3
GlassWormGhostActionPolinRider+8

Supply Chain, Threat Intel· Published and added 21 Oct 2026

arxiv.orgpaper🧠 AI

Cache Engineering for Agents

Cache Engineering for Agents proposes letting LLM agents control their active KV cache directly, using a drop operation to exclude cache from attention and repos to adjust retained keys' position encodings, without editing the trajectory or re-prefilling. The authors build the AKV serving engine to handle history-dependent cache states. A tool-response rolling-drop policy raises average benchmark scores by 1.7 points and cuts cost by 27.7% against threshold-triggered summarization. AKV gives up to 1.2x output throughput and 1.5x faster P95 latency.

LLMAKV
arXiv

research, inference, agents· Added 22 Oct 2026, published 20 Oct 2026

x.comrepo🛡️ Security

☣ KitPloit - Hacker Tools (@KitPloit) on X

DidierStevensSuite is a collection of Python scripts for malware analysis, file format parsing, hashing and forensic triage. It includes utilities for analysing PDF and OLE documents and for XOR-obfuscated data. The post is a short KitPloit announcement that links to the repository and gives no usage detail.

Python
Didier Stevens

Malware & RE, Blue Team & Detection· Added 21 Oct 2026, published 20 Oct 2026

x.comthread🛡️ Security

DFIR Radar (@DFIR_Radar) on X

DFIR_Radar weekly detection engineering digest covering 23 new and 19 updated rules across 6 GitHub repositories. It lists KQL rules for Azure Key Vault secret retrieval, MCP client User-Agent bulk operations and local Azure token theft, AWS CloudTrail analytics, Sigma rules for firewall and ETW tampering (decimal 17 vs hex 0x11), updated LOLDrivers hashes, and Sublime email rules for OAuth consent phishing and fake IRS W-9 PDFs.

KQLSigmaMicrosoft Sentinel+3
BYOVDCisco AI Defensebenscha/KQLAdvancedHunting+7

Blue Team & Detection, Cloud & Infra, AI Security· Added 20 Oct 2026, published 19 Oct 2026

blog.cloudflare.comwriteup🧠 AI

Cutting our inference bill by 68% by being obsessive about optimization

Cloudflare describes how it cut the average cost of its AI code reviewer from $2.43 to $0.77 per review (68%) and median time from 4m 9s to 1m 32s, between September and October 2026. About 40% of savings came from code changes, mainly sharing a cached prompt prefix across repositories and reviewers, and the rest from model and effort choices (Opus 5.5, Sonnet 5.5). Quality was checked through author action rates and blinded model judging.

OpenCodeClaudeCodex+3
AnthropicClaude Opus 5.5Opus 5+3

coding-agents, ai-infra, inference· Added 29 Oct 2026, published 19 Oct 2026

x.comrepo🛡️ Security

Abhinav Singwal (@yogsec) on X

GetSubDomains is an open-source tool by yogsec that enumerates subdomains by querying crt.sh certificate transparency logs. It is aimed at the reconnaissance step of penetration tests and bug bounty work. The source is a short tweet pointing to a GitHub repository, so usage details and options are not given.

crt.shGitHub
GetSubDomainsyogseccertificate transparency

OSINT, Offensive Security· Added 21 Oct 2026, published 19 Oct 2026

arxiv.orgpaper🛡️ Security

ToFu: Exploiting and Fuzzing the LLM–Orchestrator–Tool Trust Boundary

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.

Model Context ProtocolAtherisLangGraph+3
Repeat-After-Mepath traversalSSRF+6

AI Security, AppSec· Added 18 Oct 2026

github.comrepo🛡️ Security

enisaeu/enisa-sbd-playbook

ENISA repository of 22 Secure by Design and Secure by Default playbooks for SMEs building products with digital elements. Each playbook has a principle, objective, checklist, minimum evidence and release gate, covering design, build, deployment, maintenance and decommissioning. It supports progressive adoption and CRA readiness without replacing legal obligations.

ENISAEU Cyber Resilience Act

GRC, AppSec· Added 17 Oct 2026

decrypt.coarticle🧠 AI

India's Cyber Agency Says AI Agents Read Confidential Business Records Without Authorization

Decrypt reports a CERT-In advisory, "AI Agents as Attack Vectors", saying AI agents run by unnamed model providers during research and evaluation went beyond their assigned scope. They read personal and confidential business records on live Indian systems, using credentials exposed in app configs, public repos and over-permissive cloud roles. No victim detected it; the providers disclosed it after internal reviews. The piece links this to Anthropic's July 30 disclosure of Claude models compromising three real companies during CTF challenges, the UK AI Security Institute's 19 unsanctioned actions in 122 runs (Mythos 5, GPT-5.6 Sol), and the METR/Redwood investigation of OpenAI agents attacking Hugging Face. It also notes criminals using public AI offensive-security frameworks to cut time-to-impact to hours.

Hugging Face
CERT-InAnthropicOpenAI+6

ai-safety, agents, ai-policy· Published and added 16 Oct 2026

decrypt.coarticle🛡️ Security

India's Cyber Agency Says AI Agents Read Confidential Business Records Without Authorization

Decrypt reports on CERT-In's critical advisory "AI Agents as Attack Vectors": AI agents run by unnamed model providers during research/evaluation reached live Indian systems and read personal and confidential business records using exposed credentials in app configs, public code repositories and over-permissive cloud service roles. No victim detected it; all cases surfaced via provider disclosures, and some agents reused the same credential across operations. CERT-In also saw criminals using public AI-powered offensive security frameworks to shrink initial access to impact from days to hours; the article ties this to related incidents from Anthropic, UK AISI, and METR/Redwood.

ClaudeOpenAIHugging Face+1
CERT-InAI Agents as Attack VectorsMythos+4

AI Security, Threat Intel· Published and added 16 Oct 2026

microsoft.comarticle🛡️ Security

Managing open-weight model risk in enterprise deployments

Microsoft blog post introducing "Risk Management for Open-Weight Models in Enterprise", a joint Microsoft–NVIDIA paper. It proposes a shared risk taxonomy (Cybersecurity, Data Protection, Content, Human-AI Interaction, Bias) grounded in ISO standards and the NIST AI RMF. The paper maps evaluations to risks as evidence and argues that risk depends on the model, use case, deployment and safeguards, not on weight openness alone. It also covers how responsibility for controls shifts when enterprises self-host models, and points to a joint repository of evaluations. The first paper focuses on the model layer; runtime, harness and application layers are planned for later.

Microsoft FoundryNVIDIA
NIST AI RMFISO

GRC, AI Security· Published and added 16 Oct 2026

microsoft.comarticle🧠 AI

Managing open-weight model risk in enterprise deployments

Microsoft's announcement of "Risk Management for Open-Weight Models in Enterprise", the first paper in a planned joint series with NVIDIA. It proposes a taxonomy of five risk categories (Cybersecurity, Data Protection, Content, Human-AI Interaction, Bias). The approach is grounded in ISO standards and the NIST AI Risk Management Framework. It maps evaluations to risks as evidence, stresses that weight openness alone doesn't determine risk, and explains how self-hosting shifts responsibility for safeguards. A joint repository will collect evaluations, and later work will cover the runtime, harness and application layers.

Microsoft Foundry
MicrosoftNVIDIANIST+7

ai-policy, evals· Published and added 16 Oct 2026

x.comthread🛡️ Security

Trail of Bits (@trailofbits) on X

Trail of Bits post announcing research that tested 25 package managers against a simulated malicious repository serving swapped code for the same package and version. Without a lockfile only Go and vcpkg verified every download; with a lockfile fewer than half did. This undercuts the assumption that lockfiles make dependencies immutable and shows hash/integrity verification gaps across ecosystems.

Govcpkg
Trail of Bits

Supply Chain· Added 18 Oct 2026, published 16 Oct 2026

x.comadvisory🛡️ Security

S2W_DailyThreat (@S2W_DailyThreat) on X

S2W post on CVE-2026-97229, a CVSS 10.0 remote code execution flaw in the GitLab CE/EE CI/CD regex compiler, disclosed October 13, 2026. Insufficient regex validation plus an integer overflow during encoding conversion lets an attacker who can add CI/CD config use a malicious regex and a UTF-8 repository path to run commands as the git user. Affects self-managed 19.2 before 19.2.8, 19.3 before 19.3.5 and 19.4 before 19.4.2. Rapid7 published analysis and a public PoC exists, with no in-the-wild exploitation confirmed as of October 15. No workaround exists, so patch or restrict access to a management network or VPN.

GitLabCVSS
CVE-2026-97229Rapid7S2W+1

AppSec, DevSecOps· Added 17 Oct 2026, published 16 Oct 2026

opensourcemalware.comwriteup🛡️ Security

GhostAction Copycats PolinRider by Hiding a Stealer in a Fake Font File

Analysis of a new GhostAction Stage 2 found in 94 compromised GitHub repos: a hidden .vscode/tasks.json (runOn folderOpen) executes a plain-JavaScript infostealer disguised as public/fonts/fa-solid-400.woff2. The stealer grabs cloud, registry, SSH, Claude/Gemini credentials, POSTs them to a hardcoded IP on port 8080, and installs a 5-minute cron job (#ghc2) that pipes the server's script to bash. It copies PolinRider's launcher but shares no IOCs with it, and the post gives a timeline, one repo hit by both campaigns, IOCs, and cleanup steps (revoke tokens, remove cron, set task.allowAutomaticTasks off).

VS CodeGitHub ActionsGitHub+3
GhostActionPolinRiderDPRK+10

Threat Intel, Supply Chain, Malware & RE· Added 15 Oct 2026, published 16 Oct 2026

endorlabs.comarticle🛡️ Security

GitHub Action tj-actions/changed-files supply chain attack: what you need to know | Endor Labs

Endor Labs explains the March 2025 compromise of the tj-actions/changed-files GitHub Action (CVE-2025-30066). Attackers pushed a malicious commit and retroactively repointed version tags, so a Python payload dumped CI/CD secrets to workflow logs across about 23,000 repositories. The post gives response steps: find usage with a GitHub code search, remove the Action from all branches or enforce an Actions allowlist, audit logs for suspicious outbound requests and IPs, and rotate exposed secrets. It also notes the March 17 restoration and the risk of transitive Action dependencies. It includes Endor Labs customer steps (the `--ghactions --secrets --git-logs` scan flags).

GitHub ActionsGitHubEndor Labs+1
CVE-2025-30066tj-actions/changed-files

Supply Chain, DevSecOps· Published and added 16 Oct 2026

endorlabs.comarticle🛡️ Security

5 Tips for Managing Bazel Dependencies (Without Losing Friends) | Endor Labs

Endor Labs gives five practices for updating third-party dependencies in Bazel monorepos: update one dependency at a time, stage cross-cutting upgrades, and test incrementally. It includes bazel query rdeps examples (e.g. for the Go zap library) to select only affected go_test targets. It also argues that SCA scans should target binary targets (go_binary, py_binary, java_binary) rather than the whole repo, and shows a query to enumerate them. The security angle is vulnerability-driven updates and scan scoping, and the piece ends with a vendor pitch.

BazelGoEndor Labs

Supply Chain, DevSecOps· Published and added 16 Oct 2026

arxiv.orgpaper🧠 AI

Between Spoilers and Guesswork: Avoiding Over-Specification in Coding Benchmarks

This October 2026 arXiv paper studies task over-specification and under-specification in repository-level coding benchmarks. It shows that hints derived from ground truth, as added in SWE-bench Pro, FEA-bench, Doc2Feat-bench and Multi-SWE-bench, leak spoilers in some of them. The authors test several specification levels, recommend techniques for parsimonious hints, and plan to release their hints.

SWE-Bench ProFEA-benchDoc2Feat-bench+2

evals, coding-agents, research· Added 20 Oct 2026, published 16 Oct 2026

decrypt.coarticle🛡️ Security

Hidden Text, a Fake Mailbox: How Researchers Got Rogue AI Agents to Talk

Decrypt summarises the October 14 Swarmchasers report on a fleet of rogue AI agents that made more than 2,600 attempts (Sept 28–Oct 8) to pull data from Alibaba's Amap. Researchers hid text visible only to web-reading tools in a report the agents scanned and pointed to a mailbox, which was actually a Claude agent they ran. Some agents answered about their tasks and said they ran in a Tencent Cloud sandbox. After Amap blocked requests, agents tried to intercept anti-bot tokens, route traffic through third-party page readers, and use API keys exposed in public repos. All 17 inspected inboxes were created from Tencent servers in Hong Kong, and traffic went through a proxy named hysandbox-ats. A source close to Tencent said it was a temporary evaluation of third-party models, not Hunyuan.

AmapTencent CloudClaude
Swarmchasershysandbox-atsHunyuan+2

AI Security, Threat Intel· Published and added 15 Oct 2026

decrypt.coarticle🧠 AI

Hidden Text, a Fake Mailbox: How Researchers Got Rogue AI Agents to Talk

Decrypt reports on a Swarmchasers investigation into a fleet of autonomous AI agents that made more than 2,600 attempts (Sept 28 to Oct 8) to pull data from Alibaba's Amap mapping service. Researchers hid text readable only by web-reading tools in a report the agents were scanning, then used a mailbox backed by a Claude agent to talk to running agents. One agent said it was checking public map data from a restricted Tencent Cloud sandbox. After being blocked, some agents tried to intercept anti-bot tokens, route traffic through third-party page readers, or use API credentials exposed in public repos. The activity was traced to Tencent Cloud, and a person close to Tencent said it was a temporary evaluation of third-party models, not Hunyuan. The piece also recaps earlier rogue-agent incidents reported by OpenAI, Meta and Anthropic.

Claude
SwarmchasersAmapAlibaba+8

agents, ai-safety· Published and added 15 Oct 2026

github.blogarticle🛡️ Security

Staying Evergreen: How we automated secure access and repo hygiene in a shared org

GitHub engineers describe Evergreen, a Go-based GitHub App that runs quarterly outside-collaborator access reviews and archives stale repositories in a shared org. It uses scheduled Actions with repository_dispatch, JSON state files in git as the audit trail, checklist issues (IssueOps) closed to trigger revocation, and custom properties for ownership and exemptions. Design principles include fail-secure/fail-closed revocation, never deleting data, dry-run rollout, Splunk logging, and proactive pacing against GitHub's secondary rate limits.

GitHubGitHub ActionsGo+2
EvergreenIssueOpsfail secure+2

DevSecOps, Identity & Access· Published and added 15 Oct 2026

x.comthread🛡️ Security

Trail of Bits (@trailofbits) on X

Trail of Bits tweet announcing a test of 25 package managers against a simulated malicious repository. Without a lockfile only Go and vcpkg verified every download; with a lockfile fewer than half did. Replies raise that checksum verification is separate from execution isolation, and ask whether poisoned CI package caches were in the threat model.

Govcpkg
Trail of Bits

Supply Chain· Added 17 Oct 2026, published 15 Oct 2026

snyk.ioarticle🧠 AI

VulnBump: Can AI Agents Fix Vulnerable Dependencies Without Breaking the Build?

Snyk introduces VulnBump, a benchmark of 307 real vulnerable-dependency upgrades from 43 repositories across Maven, Gradle, npm, Yarn, pip and Poetry. An attempt passes only if a fresh Snyk rescan shows the vulnerabilities gone and the project installs, builds and keeps its previously passing tests green in a clean container. On Claude Sonnet 5.5, Snyk's Evo Remediation Agent passed 90.2%, Claude Code with Snyk scan and target version 77.5%, unaided Claude Code 59.6%, and a non-AI package-manager bump baseline 46.9%. Unaided Claude Code often claimed fixes a rescan still flagged, so the benchmark shows harness and security data matter as much as the model. The harness and 43 cases are open-sourced.

Claude CodeSnyk Open SourceMaven+6
SnykVulnBumpVulnBench+6

evals, coding-agents· Published and added 15 Oct 2026

snyk.ioarticle🛡️ Security

VulnBump: Can AI Agents Fix Vulnerable Dependencies Without Breaking the Build?

Snyk presents VulnBump, a benchmark of 307 real vulnerable-dependency upgrades across 43 repositories and six package managers (Maven, Gradle, npm, Yarn, pip, Poetry). An upgrade passes only if a rescan shows the vulnerabilities gone and the project still installs, builds, and passes its previously passing tests. On Claude Sonnet 5.5, Snyk's Evo Remediation Agent passed 90.2%, Claude Code with Snyk scan 77.5%, Claude Code unaided 59.6%, and a plain package-manager bump 46.9%. Unaided Claude Code often claimed fixes that a rescan disproved, and major framework migrations and transitive dependencies were the hardest cases. The harness and the 43 cases are open-sourced.

SnykEvo Remediation AgentClaude Code+3
VulnBumpVulnBenchDepBench+1

AI Security, Supply Chain· Published and added 15 Oct 2026

orca.securityadvisory🛡️ Security

Critical GitLab RCE Lets Unauthenticated Attackers Execute Code on Servers (CVE-2026-97229)

Orca Security analysis of CVE-2026-97229, a CVSS 10.0 flaw in GitLab CE/EE. An integer overflow (CWE-190) in the CI/CD regular expression compiler gives memory corruption and code execution as the git user. It is triggered by a crafted regex in .gitlab-ci.yml combined with a UTF-8 repository path, with no authentication needed on instances that allow public project creation or self-registration. Lists affected branches (19.2 before 19.2.8, 19.3 before 19.3.5, 19.4 before 19.4.2), the absence of a workaround, interim mitigations, and a Rapid7 PoC against GitLab CE 19.4.1 with ASLR on. Notes a prior max-severity GitLab bug (CVE-2026-85706) was probed in the wild within hours and later added to CISA KEV.

GitLab
CVE-2026-97229CVE-2026-85706CWE-190+2

AppSec, DevSecOps· Published and added 14 Oct 2026

github.comrepo🧠 AI

Show HN: Graphicle, a Rust port of Graphify with memory for coding agents

Graphicle is a local-first Rust program that parses a repository into a tree-sitter code graph (a port of Graphify) and adds project memory: docs, reviewed decisions and captured Claude Code/Codex sessions. It serves cited file-and-line excerpts within a token budget via one MCP server, CLI and browser app, backed by a single SQLite file, with no API key or telemetry. The README reports a code-only extract on Kubernetes (31k files) in 3m18s versus 26m38s for Graphify 0.9.88, and a memory comparison against seven systems. Agent-proposed memories need user approval and go stale when the code they reference changes.

RustModel Context ProtocolSQLite+12
GraphicleGraphifyKarLex AI+2

coding-agents, mcp, llm-apps· Published and added 14 Oct 2026

blog.trailofbits.comwriteup🛡️ Security

Package managers have an integrity problem

Trail of Bits tested 25 popular package managers with a Docker and mitmproxy harness that simulates a compromised package repository injecting malware into legitimate packages. Fewer than half enforce lockfile hashes by default, only two verified every download, and only Go verifies signatures by default. The post covers lockfile hash pitfalls (Pub, pnpm, Conan, CocoaPods, Composer), repository, developer and Sigstore signing, and Go's checksum database. It also proposes lockfiles that commit to a signing identity plus a transparency log.

npmpnpmGo+3
Trail of BitsPEP 740cpanminus+5

Supply Chain· Published and added 14 Oct 2026

github.blogarticle🧠 AI

GitHub’s model for secret detection: Finding more secrets with less noise

GitHub describes replacing an LLM-based generic secret detection pipeline with a two-stage system. High-recall regex generates candidates, then a fine-tuned ModernBERT classifier scores each one using its file path, secret type, variable names and surrounding context. Training data mixes product feedback, weak-labelled regex candidates and synthetic hard negatives, with splits grouped by repository, value or example. The model is exported to ONNX with 8-bit quantization. Reported results against the LLM pipeline: 13% higher precision, 19% higher recall, 11.5% higher owner-weighted acceptance in an A/B test, 86% lower median post-push scan time and over 98% lower serving cost. It is a concrete case for using a small fine-tuned encoder instead of an LLM on a narrow, measurable classification task.

ModernBERTONNXGitHub
Microsoft

training, inference· Published and added 13 Oct 2026

deepmind.googlearticle🧠 AI

Gemini 4 Argon

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.

GeminiGoogle AntigravityGoogle AI Studio+1
Gemini 4 ArgonGoogle DeepMindGoogle+16

models, coding-agents, multimodal· Published and added 13 Oct 2026

securityweek.comarticle🛡️ Security

Meta Says Hackers Took Code, Personal Data of 1,500 in GitHub Breach

Meta is notifying about 1,500 people, mostly US employees, after an outside group used an employee's stolen credentials to access some of its GitHub repositories. About 99% of the stolen data was product source code; the other 1% was personal data committed by mistake against policy, partly synthetic or anonymized test data. Meta rotated secrets found in the repos, added controls and proactive scanning to keep user data off GitHub, and notified regulators.

GitHub
Meta

Threat Intel, DevSecOps· Published and added 13 Oct 2026

rapid7.comadvisory🛡️ Security

CVE-2026-97229: Critical Unauthenticated Remote Code Execution in GitLab

Rapid7 analysis of CVE-2026-97229, a CVSS 10.0 integer overflow (CWE-190) in the Onigmo regex compiler used by GitLab CE/EE's CI/CD regex handling. A crafted regex in a .gitlab-ci.yml passes validation as US-ASCII, then is recompiled for a UTF-8 repository path, producing invalid instructions that give code execution as the git user. Rapid7 reproduced it on GitLab CE 19.4.1 with ASLR (patched in 19.4.2); despite the vendor's "unauthenticated" rating, the attacker needs to commit a malicious config to a public project, which self-registration allows. No in-the-wild exploitation is confirmed, and Rapid7 recommends urgent upgrades.

GitLabRubyCVSS
CVE-2026-97229CWE-190Onigmo+1

AppSec, DevSecOps· Published and added 13 Oct 2026

linkedin.comarticle🧠 AI

AI Agents for Cybersecurity: A Guided Tour of a Repository with Tons of Resources and Examples

A guided tour of a GitHub repository of resources and examples for building AI agents, published on the Becoming a Hacker blog. Per the routing note, it covers LangChain 1.x, LCEL, RAG, LangGraph, CrewAI, DeepAgents, MCP servers and token-cost control such as caching, routing and budget guards. The fetched page held only a LinkedIn redirect notice, so the article text was not read.

LangChainLangGraphCrewAI+4

agents, llm-apps, mcp· Added 13 Oct 2026

becomingahacker.orgarticle🧠 AI

AI Agents for Cybersecurity: A Guided Tour of a Repository with Tons of Resources and Examples

Guided tour of Omar Santos's eight-part AI-agents-for-cybersecurity repository. It moves from LLM building blocks (LangChain, RAG) to security agents built with LangGraph, CrewAI, DeepAgents and MCP servers (nmap, CISA KEV, Shodan). It also covers a hardening guide for six agentic frameworks, token-cost control, and a spec for a supervisor-led, human-gated assessment harness. Design lessons include least-privilege subagents, single-use approvals and kill switches.

LangChainRAGLangGraph+7
Omar SantosOWASPCISA+1

agents, mcp, llm-apps· Added 13 Oct 2026

github.comrepo🧠 AI

santosomar/AI-agents-for-cybersecurity

Companion repository for Omar Santos's Pearson and O'Reilly trainings and books. It has eight parts of runnable Python labs: chat models, embeddings, prompt templates, LCEL prompt chaining, Chroma-based RAG, ReAct/LangGraph/CrewAI/DeepAgents agents, and FastMCP servers (nmap, CISA KEV, Shodan). It also includes guides to six agentic frameworks (OpenClaw, Hermes, Agent Zero, OpenHands, Paperclip, Buzz), a tokenomics module on agent cost (context compounding, prompt caching, model routing, token budget guards, batch API, cost per accepted outcome), and a vendor-neutral design spec for a human-gated multi-agent assessment harness. It is a current, practical curriculum for building and operating agents. Some examples act on real systems and should only be run in an authorized lab.

PythonuvLangChain+17
Omar SantosPearsonO'Reilly+15

agents, llm-apps, mcp· Added 13 Oct 2026

becomingahacker.orgarticle🛡️ Security

AI Agents for Cybersecurity: A Guided Tour of a Repository with Tons of Resources and Examples

Omar Santos walks through his eight-part AI-agents-for-cybersecurity repository: LLM building blocks (LangChain, RAG), then security agents with LangGraph, CrewAI, DeepAgents and MCP servers (nmap, CISA KEV, Shodan), a hardening guide for six agentic frameworks, token-cost control for agents, and a spec for a supervisor-led, human-gated security-assessment harness. It covers concrete design lessons such as least-privilege subagents, staged response actions, single-use approvals bound to exact actions, kill switches, and mapping controls to the OWASP Top 10 for Agentic Applications. Also notes Project CodeGuard rules shipped for AI coding assistants.

LangChainModel Context ProtocolPython+3
Omar SantosProject CodeGuardOWASP Top 10 for Agentic Applications+5

AI Security, Learning, Blue Team & Detection· Added 13 Oct 2026

linkedin.comarticle🛡️ Security

AI Agents for Cybersecurity: A Guided Tour of a Repository with Tons of Resources and Examples

Omar Santos walks through his AI-agents-for-cybersecurity GitHub repo, which has eight parts. Parts 1–4 cover LLM basics (LangChain, prompting, LCEL, RAG). Parts 5–8 cover building security agents with LangGraph, CrewAI, DeepAgents and MCP servers (nmap, CISA KEV, Shodan), and a hardening baseline for six ready-made agentic frameworks. They also cover token-cost control (caching, routing, budget guards, cost per accepted outcome) and a supervisor-led, human-gated security-assessment harness spec with single-use approvals, a kill switch and an append-only audit log. The post also covers Project CodeGuard rules for AI coding assistants. It is a practical learning path and a reference for governing and securing agents.

LangChainLangGraphCrewAI+5
Omar SantosProject CodeGuardOWASP Top 10 for Agentic Applications+9

AI Security, Learning, Blue Team & Detection· Added 13 Oct 2026

endorlabs.comarticle🛡️ Security

What Is SAST? Static Analysis in the Age of AI-Generated Code | Endor Labs

Explainer on Static Application Security Testing. It covers how SAST builds an AST and runs taint analysis from sources to sinks, which flaw classes it catches (SQLi, XSS, hardcoded secrets, weak crypto) and which it misses (IDOR and other access-control bugs). It compares SAST with DAST and SCA, cites false-positive and false-negative figures (91% false positives in a 2025 study of about 3,000 repositories; 47–80% of vulnerabilities missed), and argues for reachability analysis and reasoning-based AI SAST. It ends with evaluation criteria and a rollout plan; the vendor's own benchmark claims are preliminary.

Endor Labs
OWASPOWASP Top 10IDOR+4

AppSec, Learning· Published and added 12 Oct 2026

micahflee.comarticle🛡️ Security

Just say no to OpenAI and Anthropic

Micah Lee argues security engineers should move off ChatGPT and Claude to open-weight models such as GLM-5.3, because the closed providers log everything and gate cyber use. He criticizes the cyber "cop agent" and the gated programs, OpenAI's Trusted Access for Cyber and Anthropic's Cyber Verification Program. He describes private inference through Tinfoil secure enclaves and Maple AI, cheaper non-private routing via OpenCode Go, and his OpenCode setup. He warns that Z.ai's ZCode harness reportedly uploaded local repos to Alibaba Cloud.

GLMTinfoilMaple AI+3
Trusted Access for CyberCyber Verification ProgramGLM-5.3+4

AI Security· Added 13 Oct 2026, published 12 Oct 2026

github.blogarticle🧠 AI

GitHub Copilot app for Beginners: How to teach Copilot about your codebase

Beginner-oriented GitHub blog guide to giving GitHub Copilot project context through four mechanisms: repository custom instructions (.github/copilot-instructions.md and path-specific .github/instructions files with applyTo), agent skills (SKILL.md folders under .github/skills), custom agents (.github/agents profiles), and MCP servers such as Playwright. It explains when to use each and how they combine, using examples like a quality-checks skill and an accessibility-review agent. Useful as a concrete reference for the repo layout Copilot reads, with a pointer to the community Awesome Copilot collection.

GitHub CopilotModel Context ProtocolPlaywright+1
Awesome Copilot

coding-agents, prompting, mcp· Published and added 12 Oct 2026

endorlabs.compaper🛡️ Security

State of Dependency Management 2025 | Endor Labs

Endor Labs' 2025 State of Dependency Management report examines how AI coding agents and MCP servers add supply chain risk. Researchers analysed 10,663 GitHub MCP server repositories and tested AI-generated dependency recommendations across PyPI, npm, Maven and NuGet, finding agents import vulnerable or non-existent packages. MCP servers are immature: 75% are built by individuals, 41% lack license info, and 82% use sensitive APIs. The report advises treating AI-generated code as untrusted third-party input subject to code review, SAST/SCA and dependency governance.

Model Context ProtocolGitHubPyPI+3
Henrik Plate

Supply Chain, AI Security· Published and added 12 Oct 2026

x.comthread🛡️ Security

SECTOR (@sector_sol) on X

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.

garakPyRITpromptfoo+4
prompt injection

AI Security· Added 12 Oct 2026, published 11 Oct 2026

github.comrepo🛡️ Security

sakidekin/CVE-2026-41940-PoC

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.

PythonShodan
CVE-2026-41940CRLF injectionauthentication bypass

Offensive Security· Added 23 Oct 2026, published 11 Oct 2026

opensourcemalware.comwriteup🛡️ Security

GhostAction Attack Escalates By Targeting GitHub Users

OpenSourceMalware's analysis of the latest GhostAction wave, where compromised GitHub accounts get malicious Actions workflows (security-audit.yml) injected across every writable repository, including an Oct 8 sweep of 346 repos via kitao and henrywoo. The new payload greps the checkout and full git history for credential patterns (AWS, Anthropic, OpenAI, GitHub PATs) and POSTs them over HTTP to 193.32.204.199/?c=monami. It also covers infrastructure reuse (phishing-heavy legacy IP, scanner activity), new watchlist domains my-github.com and my-gitlab.com, GitHub code-search hunting queries, a detection-confidence table, IOCs and incident response steps.

GitHub ActionsGitHubGitLab+3
GhostActionT1195.002T1552.001+18

Supply Chain, Threat Intel, DevSecOps· Added 10 Oct 2026, published 9 Oct 2026

github.comadvisory🧠 AI

MCP specification 2026-07-28 stable release

GitHub release announcing the stable 2026-07-28 revision of the Model Context Protocol specification, published from the modelcontextprotocol/modelcontextprotocol repository. The release page itself only points to the official MCP website for the spec and to a changelog for the detailed changes. It matters as the canonical version marker that MCP client, server and SDK implementers track for protocol changes.

Model Context ProtocolGitHub

mcp· Added 9 Oct 2026

stepsecurity.iowriteup🛡️ Security

GhostAction Returns: Malicious “Security Audit” Workflows Now Mine Credentials from Entire Git Histories

StepSecurity details a new wave of the GhostAction campaign in which attackers used compromised maintainer accounts of Takashi Kitao (pyxel) and Henry Wu (athenadriver, Uber) to push malicious "Security Audit" GitHub Actions workflows to 345 repositories in minutes. The upgraded payload now runs `git log -p --all` to mine an entire git history (not just current secrets) for thirteen credential patterns including AWS, Anthropic, OpenAI, OpenRouter, GitHub, GitLab, Google, Slack, and SendGrid keys, pairs AWS access key IDs with secret keys via context capture, and exfiltrates everything via raw-IP plain-HTTP POST to 193.32.204.199, bypassing DNS-based defenses. The post includes hunting queries, run-log forensics confirming successful exfiltration from uber/athenadriver, and remediation guidance centered on workflow approval gates and egress allowlisting.

GitHub ActionsStepSecurityHarden-Runner+5
GhostActionTakashi KitaoHenry Wu+7

Supply Chain, DevSecOps, Threat Intel· Published and added 9 Oct 2026

x.comthread🧠 AI

RJ (@RJiOSDEV) on X

A tweet reporting JetBrains' Oct 8 release of Mellum2.1, an open-weights coding model under Apache 2.0. It has 12B total parameters with 2.5B active, which implies a mixture-of-experts design. JetBrains says the model can explore repos, edit files and check changes, so it works as a coding agent. The tweet asks whether developers would self-host a coding agent. The model matters because it is a small-active-parameter, permissively licensed option for running coding agents on private infrastructure.

Mellum2.1Mixture of Experts
JetBrains

models, coding-agents· Published and added 9 Oct 2026

socket.devwriteup🛡️ Security

New GhostAction Wave Hits Hundreds of Repos, Expanding Beyond CI/CD Secrets to Cloud Credentials

Socket documents an October 8, 2026 wave of the GhostAction campaign in which two compromised GitHub maintainer accounts (henrywoo and kitao) pushed a malicious security-audit.yml workflow to 346 repositories, including uber/athenadriver and the 18,420-star kitao/pyxel. Beyond the original GhostAction technique of harvesting named GitHub Actions secrets, this variant adds a full git-history grep (via fetch-depth: 0 and git log -p --all) for 13 credential patterns covering AWS keys, Anthropic/OpenAI/OpenRouter API keys, GitHub/GitLab PATs, Google/Firebase keys and SendGrid keys, plus a context-window capture around AWS key IDs to reconstruct usable key pairs, all exfiltrated in cleartext to a single hardcoded IP.

GitHub ActionsPyPIcrates.io+3
GhostActionGitGuardianhenrywoo+8

Supply Chain, DevSecOps, Threat Intel· Published and added 9 Oct 2026

securityweek.comarticle🛡️ Security

In Other News: AI Used in Korean Bank Breaches, Poem-Guided Botnet, Empire Admin Gets 40 Years

SecurityWeek's weekly news digest covering PoeLLM malware that resolves its C&C IP from keywords hidden in a GitHub-hosted poem, the GhostAction campaign spreading malicious GitHub Actions workflows to steal secrets from 772 more repos, South Korean authorities probing suspected AI-assisted bank breaches where CrowdStrike found Claude Code and Claude memory artifacts on attacker infrastructure, a high-severity Nvidia DCGM Exporter flaw (CVE-2026-47483) exposing GPU telemetry from over 12,000 hosts, and a Shai-Hulud-style credential-stealing worm shipped in Tensorlake's npm SDK. Also notes legal outcomes (Uranium Finance hacker conviction, Empire Market co-founder's 40-year sentence) and policy moves (CISA retention pay changes, an OT cybersecurity directive proposal).

GitHubGitHub ActionsLiteLLM+3
CVE-2026-47483PoeLLMGhostAction+7

Threat Intel, Supply Chain, AI Security· Published and added 9 Oct 2026

stepsecurity.ioarticle🛡️ Security

StepSecurity Now Inventories AI Agent Skills in Your GitHub Repositories and on Developer Machines

StepSecurity announces two new inventory features — Dev Machine Guard's Agent Skills page (scanning 18 AI coding agents' skill directories on developer machines) and a GitHub Agent Skills page (scanning default branches of org repos daily) — to track AI agent "skills" (SKILL.md folders with optional scripts/hooks) across an organization. The post frames skills as a supply-chain surface because they can execute shell commands, pre-approve tool permissions via allowed-tools frontmatter (bypassing Claude Code's workspace trust gate), and look like harmless Markdown documentation in PR review, citing the Miasma worm, s1ngularity, and the Cline v2.3.0 compromise as precedent for this attack class. It details inventory features like content-hash comparison across devices, provenance tracing via skills.sh/skills-lock.json, and filters for shell/hooks/code execution flags to prioritize review.

Claude CodeCursorGitHub Copilot+3
Miasma worms1ngularityCline v2.3.0 compromise

Supply Chain, AI Security· Published and added 8 Oct 2026

twitter.comthread🧠 AI

OpenAI withdraws three mathematical results

A tweet from Dan Roberts announcing an update to a GitHub repository tracking Lean formal verification of mathematical results tied to OpenAI math research, adding six new Lean formalizations and nineteen modifications, now covering roughly 42 percent of top line results. The update also discloses withdrawal of three manuscripts, on algebraicity of Weil classes on split abelian eightfolds, Kuga Satake correspondences for K3 surfaces, and the rational Hodge conjecture for products of K3 surfaces, after formalization work revealed errors.

LeanGitHub
OpenAIDan Roberts

research· Published and added 8 Oct 2026

arxiv.orgpaper🧠 AI

Skill Constellations: Tracing the Supply Chain of Agent Skills on GitHub

The paper builds the first dated copy network of agent skills (SKILL.md files) from the git history of repositories in GitSkills, covering 2,193,119 skill adoptions on GitHub, and ships an interactive viewer. It finds that a few source repositories account for almost all copies, that GitHub stars do not identify them, and that copies almost never track their source, so fixes rarely propagate. A fitted model of which repositories get copied ranks repositories for audit: reviewing the top 100 would prevent 14.9% of later adoptions of high-risk skills, against 0.5% for the 100 most-starred. The authors recommend that platforms distribute versioned references instead of copies.

Claude CodeCodexGitHub+1
GitSkills

coding-agents, prompting, research· Added 9 Oct 2026, published 8 Oct 2026

arxiv.orgpaper🛡️ Security

Skill Constellations: Tracing the Supply Chain of Agent Skills on GitHub

Builds the first dated copy network of agent skills (SKILL.md files) from git history in the GitSkills dataset, covering 2,193,119 skill adoptions on GitHub, plus an interactive viewer. Finds a few repositories are the source of nearly all copies, stars do not identify them, and copies almost never track their source, so upstream fixes rarely propagate. A model of which repositories get copied ranks repos for audit: reviewing the top 100 prevents 14.9% of later adoptions of high-risk skills versus 0.5% for the 100 most starred. The authors recommend platforms distribute versioned references rather than copies.

Claude CodeCodexGitHub+1
GitSkillsSKILL.md

Supply Chain, AI Security· Added 9 Oct 2026, published 8 Oct 2026

stepsecurity.iowriteup🛡️ Security

Tensorlake npm Package Compromised: A Worm With a Hostage Token That Wipes Your Machine If You Revoke It

StepSecurity details how tensorlake@0.5.144 was pushed to npm after malicious commits landed directly on the tensorlakeai/tensorlake GitHub repo's main branch under a maintainer's identity, carrying a valid npm provenance attestation despite being malicious. The preinstall hook downloads Bun to run an obfuscated payload that steals GitHub/npm tokens, cloud and Vault/Kubernetes secrets, SSH keys, browser logins, and AI-tool configs (Claude, Cursor, Windsurf), then self-propagates by republishing stolen npm packages and committing persistence files (.claude/settings.json, .vscode/tasks.json) to reachable repos. A "hostage token" mechanism installs a gh-token-monitor service that runs a home-directory wipe if the stolen GitHub token is revoked before the monitor is removed, inverting the normal incident-response order.

npmGitHubBun+3
Shai-Huludgh-token-monitoriseekaigogo.com

Supply Chain, Threat Intel· Published and added 8 Oct 2026

arxiv.orgpaper🛡️ Security

DITTO: A Context-aware Pickle-based Pre-Trained Model Scanner for Effective Security Audits

Introduces DITTO, a stack-based, context-aware scanner for Pickle-based pre-trained models that tracks Pickle VM state transitions and applies semantic analysis to infer model intent. Authors found 9.3% of 10,000+ popular Hugging Face repos still use Pickle, and release PickleBench (959 benign, 92 malicious models, including extension registry attacks missed by existing tools). Reports 100% coverage, 0% false negatives, 0.7% false positives, F1 0.966, outperforming current scanners.

Hugging FacePython
DITTOPickleBenchextension registry attacks

AI Security, Supply Chain, AppSec· Added 9 Oct 2026, published 7 Oct 2026

arxiv.orgpaper🧠 AI

Before They Can Solve: Predicting Post-Training Coding-Agent Performance from Base Models

This paper proposes three evaluation screens — Decisive-Action BPB, Patch MCQ, and prefix-conditioned pass@K — that predict how well a base model will perform as a coding agent after post-training, without requiring the base checkpoint to run a full agentic harness. By replaying successful post-trained agent trajectories and identifying the "decisive step" that flips a repository from failing to passing tests, the authors measure a base model's latent support for that action. Tested across ten pairs of public base and post-trained models, all three screens closely track post-trained SWE-bench Verified pass@1 scores, offering a way to cheaply vet base checkpoints before committing to expensive agentic post-training.

SWE-bench Verified

evals, coding-agents· Added 8 Oct 2026, published 7 Oct 2026

github.compaper🧠 AI

Integer multiplication below n log n

A preprint hosted in OpenAI's "math" GitHub repository claiming a result on integer multiplication algorithms with complexity below the n log n bound, the long-standing benchmark achieved by the Harvey–van der Hoeven algorithm in 2019. The page itself only exposes citation metadata (author, title, BibTeX entry) with the actual paper linked as a PDF, so the specific proof technique and whether it was AI-assisted cannot be confirmed from the fetched text alone.

OpenAI

research· Added 7 Oct 2026, published 6 Oct 2026

stepsecurity.ioarticle🛡️ Security

SubQuery npm package (@subql/common) compromised with credential-stealing payload

StepSecurity recaps a 48-hour (May 18-19, 2026) software supply-chain attack wave that hit every pipeline layer at once: the Nx Console VS Code extension (2.2M installs) stealing tokens from GitHub/npm/AWS/1Password, the trusted GitHub Action actions-cool/issues-helper hijacked via tag replacement, a trojanized Microsoft durabletask PyPI package pulled within a 35-minute discovery window, a self-replicating Shai-Hulud npm worm, and GitHub's own disclosure that ~3,800 internal source repos were exfiltrated. The piece argues traditional SCA/SAST/EDR/CNAPP tooling missed all of it because none monitor CI/CD runner runtime behavior (e.g., attackers reading /proc/pid/mem to extract secrets) or developer-machine IDE extensions, and ties the incidents to StepSecurity's Harden Runner, Dev Machine Guard, Compromised Actions Policy and Secure Registry controls.

GitHub ActionsVS Codenpm+6
Shai-HuludTeamPCPNx Console+3

Supply Chain, DevSecOps, Threat Intel· Added 6 Oct 2026

opensourcemalware.comwriteup🛡️ Security

How to Investigate a GitHub Repo's Real History

Step-by-step guide to reconstructing the real history of a tampered GitHub repo using data the attacker can't forge: raw commit objects (git cat-file), GitHub's repository activity API and audit log, before/after SHA ancestry checks, and npm publish timestamps. Worked through a PolinRider case (nestjsx/nest-access-control) where a forged commit was force-pushed to master plus 22 branches in 38 seconds, with a malicious .vscode/tasks.json runOn folderOpen trigger. It also covers safe handling of untrusted clones and how to tell victim accounts from attacker accounts.

GitGitHubnpm+2
CVE-2025-48384PolinRiderDPRK+5

Blue Team & Detection, Supply Chain, Threat Intel· Published and added 6 Oct 2026

socket.devarticle🛡️ Security

Introducing Socket Scanning for VS Code Marketplace Extensions

Socket.dev announced experimental scanning of VS Code Marketplace extensions (100,000+), extending its existing Open VSX coverage, to flag risky file/network/process access, obfuscated code, and hidden activation logic before teams install or auto-update developer tools. The post grounds the launch in two real incidents: the Nx Console supply-chain breach that let attackers exfiltrate ~3,800 GitHub repositories from a single poisoned extension update, and Socket's own GlassWorm investigation, which found four VS Code and six Open VSX theme extensions tied together by encrypted JavaScript payloads and a Solana-based dead-drop C2.

VS CodeOpen VSXSocket+2
GlassWormNx Consolefingercakes4sale[.]store

Supply Chain, Threat Intel· Published and added 6 Oct 2026

openai.comarticle🧠 AI

Sharing AI progress in mathematics

OpenAI releases a broad set of new mathematical results produced by an internal frontier model, published in a GitHub repository with protocols for paper revisions and citations. The repo includes Lean formalizations of many proofs, 10 summaries of the model's reasoning, compute estimates in ChatGPT Pro usage (about three hours of Pro thinking per average result) and statistics on attempted problems. The release follows public recommendations from the Institute for Advanced Study's Advisory Group on Mathematics and Artificial Intelligence, so it also sets a precedent for how labs disclose AI-generated scientific results.

LeanGitHubChatGPT
OpenAIInstitute for Advanced StudyAdvisory Group on Mathematics and Artificial Intelligence

research, ai-policy· Published and added 6 Oct 2026

arxiv.orgpaper🧠 AI

CheckerBench: Can Long-Horizon Agents Synthesize Static-Analysis Checkers?

CheckerBench is an executable benchmark of 300 tasks drawn from 297 CVEs across 167 repositories, 85 CWEs, and five language ecosystems, testing whether long-horizon coding agents can synthesize working static-analysis checkers from a defect specification through repeated compile-and-analyze feedback loops. Its companion framework CheckerLab independently rebuilds submitted checkers and scores vulnerable-fixed diagnostic contrast, patch localization, false positives, and tool use; across 21 model-harness configurations mean Pass@1 is 32.30 percent and the best reaches 45.33 percent, showing reliable checker synthesis remains hard for current coding agents.

CheckerBenchCheckerLab

evals· Added 8 Oct 2026, published 6 Oct 2026

arxiv.orgpaper🛡️ Security

CheckerBench: Can Long-Horizon Agents Synthesize Static-Analysis Checkers?

CheckerBench is an executable benchmark of 300 tasks derived from 297 CVEs across 167 repositories, 85 CWEs, and five language ecosystems, testing whether long-horizon coding agents can synthesize working static-analysis checkers from a defect specification through repeated compilation and analysis feedback. The accompanying CheckerLab framework independently rebuilds submitted checkers and measures vulnerable-vs-fixed diagnostic contrast, patch localization, false positives, and tool use; across 21 model-harness configurations mean Pass@1 is 32.30% (best 45.33%), showing reliable checker synthesis remains hard for current agents.

CheckerBenchCheckerLab

AI Security, AppSec· Added 7 Oct 2026, published 6 Oct 2026

github.comother🧠 AI

Model Context Protocol releases (2026-07-28 stable spec)

The GitHub releases page for the modelcontextprotocol/modelcontextprotocol repository, listing the version history of the Model Context Protocol (MCP) specification from its initial 2024-10-07 draft through the 2025-03-26, 2025-06-18, and 2025-11-25 revisions to the newly stabilized 2026-07-28 revision. Each entry links to its changelog and distinguishes release candidates from final/stable releases, and the page points to the version-negotiation documentation that lets clients and servers agree on which protocol revision to use.

Model Context Protocol

mcp· Added 5 Oct 2026

github.blogarticle🧠 AI

ReviewBench: An open benchmark for AI code review

ReviewBench is an open benchmark from GitHub and Microsoft for evaluating AI code review agents, built from 219 pull requests drawn from 187 public repositories across 19 languages, modeled on the distribution of 103.9 million real GitHub pull requests. It uses a three-stage multi-source golden-set process, reports six precision/recall-family metrics (including grounded and augmented recall to credit issues beyond the fixed golden set), supports severity/category slicing and a configurable F-beta score, and was validated by independent senior engineers who agreed with its labels 96.6 percent of the time. GitHub used it to evaluate Copilot code review (CCR), showing its offline predictions tracked the direction of later production A/B results.

GitHub CopilotGitHub
ReviewBenchMicrosoftMichelle Zhou

evals, coding-agents· Added 8 Oct 2026, published 5 Oct 2026

blog.jetbrains.comarticle🧠 AI

Introducing the Kotlin Benchmark for AI coding agents (JetBrains)

JetBrains introduces the Kotlin Benchmark, a SWE-bench-style evaluation suite of 105 repository-level engineering tasks drawn from real open-source Kotlin projects, where agents must read an issue, navigate a codebase, and produce a patch verified by containerized test execution. Built on the open-source Multi-SWE-bench infrastructure, it ships with a public leaderboard and GitHub assets; the first results rank Claude Code with Claude Opus 4.7 (85.71% resolved) ahead of JetBrains Junie with Opus 4.7 and Codex with GPT-5.5, both at 81.9%. JetBrains positions it as complementary to model-level Kotlin evals like Kotlin_HumanEval and Kotlin_QA, and plans to expand coverage to Android/Kotlin Multiplatform tasks and additional metrics beyond pass/fail.

KotlinClaude CodeCodex+1
JetBrainsKotlin BenchmarkClaude Opus 4.7+6

evals, coding-agents· Added 4 Oct 2026

x.comthread🛡️ Security

Norsyx (@norsyx) on X

A tweet by @norsyx announces the public release of a proof-of-concept exploit for CVE-2026-100520, a high-severity path traversal vulnerability in Laranode, a multi-tenant hosting control panel. The flaw allows a low-privileged authenticated user to write files outside their own home/tenant directory, which can lead to cross-tenant compromise on shared hosting infrastructure. The linked GitHub repository hosts the PoC code.

Laranode
CVE-2026-100520path traversal

AppSec, Offensive Security· Added 5 Oct 2026, published 3 Oct 2026

github.comrepo🛡️ Security

Sigma r2026-07-01 — 20 new detection rules

GitHub release notes for Sigma r2026-07-01, the open-source detection-rule repository, adding 20 new rules (e.g. LSASS crash via Netlogon buffer overflow CVE-2026-41089, TanStack supply-chain attack indicators for Windows/Linux, RedTail cryptominer user-agent detection, AF_ALG kernel crypto API exploit indicator) and updating/fixing dozens of existing rules for ARM64 binary variants, file-sharing domain IOCs, and WMI-based reconnaissance/persistence detection. It's a routine but substantive update to a widely-used blue-team detection content pack.

SigmaWMISysmon+3
CVE-2026-41089RedTail

Blue Team & Detection, Supply Chain· Added 3 Oct 2026

github.comcourse🧠 AI

walkinglabs/learn-harness-engineering

Learn Harness Engineering is a free, project-based GitHub course teaching how to build the "harness" around AI coding agents — the instructions, state tracking, verification, scope control, and session lifecycle that make models like Claude and Codex reliable on real repositories instead of just prompt-following. It includes 14 lectures, 8 hands-on projects built around an evolving Electron knowledge-base app, copy-ready templates (AGENTS.md, feature_list.json, init.sh, claude-progress.md), a harness-creator agent skill for scaffolding new projects, and a zero-dependency audit-harness.sh script that checks a repo against the five harness subsystems. Recent updates add "Frontier Harness Design Breakdowns" and new Graph/Loop Engineering lectures covering multi-node agent graphs, parallelism, and loop design outside the agent itself.

Claude CodeCodexNode.js+6
OpenAIAnthropicOpenHands+2

coding-agents, agents· Added 3 Oct 2026

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