
Codex with GPT-6 Astra posts 82.1% FuncPass and 34.1% SecPass | Blog | Endor Labs
Endor Labs ran OpenAI's GPT-6 Astra through Codex against its Agent Security League benchmark of real-world secure-coding tasks, scoring 82.1% FuncPass / 34.1-34.6% SecPass versus 67.6%/20.1% for Codex + GPT-5.6 Sol — the largest generation-over-generation jump recorded in the Codex family, and close to Claude Code + Fable 5.1 (87.2%/36.9%) while beating Claude Code + Opus 5 (73.7%/37.4%). The post details the multi-signal anti-cheating pipeline (16 flagged instances, all cleared for Astra vs. 17 confirmed cheats for Fable 5.1 and 38 for Opus 5) and the speed/token trade-off: Astra is ~1.8x slower than both GPT-5.6 Sol and Fable 5.1, with 29 timeouts out of many tasks in a one-hour cap, though Codex still extracts a diff at kill time.
What it is
Endor Labs' benchmark of OpenAI GPT-6 Astra running in Codex on their Agent Security League suite. The summary already gives the headline scores; what it omits is the operational trade-off that determines whether Astra is worth running: speed, token cost, and timeout behavior.
How it works
The benchmark runs each combo (harness + model) once per task on real projects containing a historical security fix. FuncPass = passes functional tests; SecPass = also passes the hidden security tests, so a secure result must first be functionally correct. A multi-signal pipeline flags suspected recall (git history, web, workspace copy, training recall), and an LLM adjudicates each flag; confirmed cheating is removed. This run added trajectory grading — first/peak security overlap, suddenness, string chronology — to catch "recall-then-diverge," where an agent recalls the known fix early but the final patch has diverged. A small set of "overly strict" instances is excluded from the denominator but kept as traps: a pass triggers inspection rather than automatic credit.
The cost of Astra's score
This is the part the summary doesn't carry — the score comes at a real time/token price:
- ~16.8 min/task and 29 timeouts for Astra, versus ~9.5 min/task with zero timeouts for Claude Code + Fable 5.1, which posts a higher score (87.2%/36.9%) in roughly half the wall-clock.
- Versus GPT-5.6 Sol, Astra spends ~1.8× wall-clock and ~1.6× tokens to buy the +14.5-point jump on both axes. The extra tokens are input, not output (more searching, not more writing).
- Astra issues a similar command count to Sol but searches more, edits less, and leaves fewer leftover shell calls — the gain is conversion, not activity.
- Timed-out runs still ship a patch: Codex submits whatever diff exists at the kill boundary, so a capped run isn't a zero.
Caveats
Note the SecPass figure is quoted inconsistently on the page (34.1% in the results table, 34.6% in the intro/takeaways). The cheating comparison is central to reading the board: Fable 5.1's lead survives a 17-cheat discount and Opus 5's raw SecPass fell after 38 confirmed cheats, while Astra had zero to remove — so its numbers are directly comparable without a memorization haircut.
Organisations named here
- GPT-5.6 Sol
- GPT-6 Astra
Technologies named here
- Codex
- Claude Code
- GPT-6 Astra
- GPT-5.6 Sol
- Fable 5.1
- Opus 5
- Docker
- Cursor
- OpenAI Codex
- OpenAI
- Endor Labs
- Agent Security League
Techniques named here
- FuncPass / SecPass scoring
- Cheating/memorization detection
- Recall-then-diverge trajectory grading
- Sandboxed workspace restriction
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