Benchmark Almanac

ExploitBench

GPT-6 Astra 100% leads since September 2026
Claude Mythos Preview 78% leads since May 2026
GPT-6 Astra 100% leads since September 2026
In use

41 recent V8 JavaScript-engine N-day vulnerabilities. Progress measured by 16 grader-verified capability flags across five tiers.

41 real V8 N-day vulnerabilities with production mitigations on. 16 binary capability flags over five tiers: coverage, bug triggering, V8 internal primitives, general primitives and arbitrary code execution. Flags are checked by oracles compiled into a patched d8 binary. Episodes cap at 300 turns. Saturated by GPT-6 Astra at 100%, and OpenAI built a post-cutoff internal port to check contamination.

Released
May 2026
Kind
Finding and exploiting real bugs
Level
Expert
Scored
Checked automatically
Answers
Agent task
Tasks
All public
Strongest model tested
GPT-6 Astra #3 on the capability index
Last in a launch post
November 2026
Last model added
November 2026
Scores refreshed
November 12th, 2026

In the authors’ words

Exploitation is not a binary event. It is a ladder of acquiring progressive capabilities, from executing a single buggy line of code to taking full control of the target. However, existing LLM security benchmarks treat a crash as exploitation success. That single binary outcome collapses the hard parts of exploitation: the transition from triggering a bug to constructing reusable primitives and control. We present ExploitBench, a capability-graded benchmark that decomposes exploitation into 16 measurable flags, from coverage and crash through sandbox primitives, arbitrary read/write, control-flow hijack, and arbitrary code execution. Each capability is verified by a deterministic oracle that uses a per-run randomized challenge-response for primitives, differential execution against ground-truth binaries to measure progress, and a signal-handler proof for code execution. We instantiate ExploitBench on 41 V8 bugs because V8 is both widely deployed and exploitation-hardened. We report three arms: <model,env> as the primary measurement of model-environment capability, <model,env, adaptive coaching> as a secondary arm that adds adaptive coaching to test whether targeted feedback shifts outcomes, and <model,env,harness> as an ablation that swaps in the model's native CLI to check whether vendor-side optimizations increase exploitation capabilities. Our results show a sharp capability split between publicly deployed frontier models and the private frontier. Across the 8 publicly deployed models tested, reaching the vulnerable code and triggering a crash is routine, but arbitrary code execution is not. The private model shows arbitrary code execution on approximately half. Overall, results suggest that exploit construction against hardened targets is an emerging frontier capability.

Abstract of ExploitBench: A Capability Ladder Benchmark for LLM Cybersecurity Agents (arXiv:2605.14153, CC0)
21
Models scored in lab cards
7
Launch posts list it, from 5 labs
26
System cards report it, from 6 labs

2 models share the top score of 100%

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

Claude Mythos Preview leads with 78% across all independent runs

Best score per model across the official leaderboard, Epoch AI’s own runs and any board Epoch AI copied. Each bar and row names its source.

GPT-6 Astra leads with 100%, claims included

Best score per model from every source, including labs’ own numbers and claims Epoch AI collected from reports and papers. Labs pick their own settings, so a claim can beat an independent run of the same model.

  1. 1 GPT-6 Astra 100%
  2. 2 GPT-6 Cyber 100%
  3. 3 GPT-6.1 Sol 99.7%
  4. 4 GPT-6.1 Terra 97.1%
  5. 5 Claude Opus 5.5 91%
  6. 6 Gemini 4 Argon 87%
  7. 7 GPT-6 Sol 82.6%
  8. 8 Claude Sonnet 5.5 80%
  9. 9 Kimi K3.1 Pro 74.7%
  10. 10 Claude Opus 5 70%
  11. 11 Muse Wonder Full 58.9%
  12. 12 GLM-5.3 54.4%
  13. 13 GPT-5.6 Terra 52.9%
  14. 14 Claude Haiku 5.5 49%
  15. 15 MiMo-V2.6 Pro 47.9%
  16. 16 GPT-6 Luna 46.2%
  17. 17 SWE-2 Flash 34.8%
  18. 18 GPT-5.6 Luna 33.2%
  19. 19 Kimi K3 32%
  20. 20 Claude Sonnet 5 31%
  21. 21 Muse Spark 1.3 28.7%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 GPT-6 Astra 100% Sep 2026 Lab model card
2 GPT-6 Cyber 100% Nov 2026 Lab model card
3 GPT-6.1 Sol 99.7% Sep 2026 Lab model card
4 GPT-6.1 Terra 97.1% Oct 2026 Lab model card
5 Claude Opus 5.5 91% Sep 2026 Lab model card
6 Gemini 4 Argon 87% Oct 2026 Lab model card
7 GPT-6 Sol 82.6% Oct 2026 Lab model card
8 Claude Sonnet 5.5 80% Sep 2026 Lab model card
9 Kimi K3.1 Pro 74.7% Oct 2026 Lab model card
10 Claude Opus 5 70% Jul 2026 Lab model card
11 Muse Wonder Full 58.9% Oct 2026 Lab model card
12 GLM-5.3 54.4% Aug 2026 Lab model card
13 GPT-5.6 Terra 52.9% Jul 2026 Lab model card
14 Claude Haiku 5.5 49% Oct 2026 Lab model card
15 MiMo-V2.6 Pro 47.9% Sep 2026 Lab model card
16 GPT-6 Luna 46.2% Oct 2026 Lab model card
17 SWE-2 Flash 34.8% Nov 2026 Lab model card
18 GPT-5.6 Luna 33.2% Jul 2026 Lab model card
19 Kimi K3 32% Jul 2026 Lab model card
20 Claude Sonnet 5 31% Jun 2026 Lab model card
21 Muse Spark 1.3 28.7% Oct 2026 Lab model card
#ModelScoreSettingDateSource
1 Claude Mythos Preview 78% AutoNudge Apr 2026 Official leaderboard
2 GPT-5.5 72% Codex, AutoNudge Apr 2026 Official leaderboard
3 Claude Opus 4.7 28% AutoNudge Apr 2026 Official leaderboard
4 Claude Sonnet 4.6 26% AutoNudge Feb 2026 Official leaderboard
5 Gemini 3.1 Pro 26% baseline Feb 2026 Official leaderboard
6 GLM-5.1 18% AutoNudge Apr 2026 Official leaderboard
7 Kimi K2.6 18% AutoNudge Apr 2026 Official leaderboard
8 Claude Haiku 4.5 14% AutoNudge Oct 2025 Official leaderboard
9 MiniMax-M2.7 13% baseline Mar 2026 Official leaderboard
#ModelScoreSettingDateSource
1 GPT-6 Astra 100% Sep 2026 Lab model card
2 GPT-6 Cyber 100% Nov 2026 Lab model card
3 GPT-6.1 Sol 99.7% Sep 2026 Lab model card
4 GPT-6.1 Terra 97.1% Oct 2026 Lab model card
5 Claude Opus 5.5 91% Sep 2026 Lab model card
6 Gemini 4 Argon 87% Oct 2026 Lab model card
7 GPT-6 Sol 82.6% Oct 2026 Lab model card
8 Claude Sonnet 5.5 80% Sep 2026 Lab model card
9 Claude Mythos Preview 78% AutoNudge Apr 2026 Official leaderboard
10 Kimi K3.1 Pro 74.7% Oct 2026 Lab model card
11 GPT-5.5 72% Codex, AutoNudge Apr 2026 Official leaderboard
12 Claude Opus 5 70% Jul 2026 Lab model card
13 Muse Wonder Full 58.9% Oct 2026 Lab model card
14 GLM-5.3 54.4% Aug 2026 Lab model card
15 GPT-5.6 Terra 52.9% Jul 2026 Lab model card
16 Claude Haiku 5.5 49% Oct 2026 Lab model card
17 MiMo-V2.6 Pro 47.9% Sep 2026 Lab model card
18 GPT-6 Luna 46.2% Oct 2026 Lab model card
19 SWE-2 Flash 34.8% Nov 2026 Lab model card
20 GPT-5.6 Luna 33.2% Jul 2026 Lab model card
21 Kimi K3 32% Jul 2026 Lab model card
22 Claude Sonnet 5 31% Jun 2026 Lab model card
23 Muse Spark 1.3 28.7% Oct 2026 Lab model card
24 Claude Opus 4.7 28% AutoNudge Apr 2026 Official leaderboard
25 Claude Sonnet 4.6 26% AutoNudge Feb 2026 Official leaderboard
26 Gemini 3.1 Pro 26% baseline Feb 2026 Official leaderboard
27 GLM-5.1 18% AutoNudge Apr 2026 Official leaderboard
28 Kimi K2.6 18% AutoNudge Apr 2026 Official leaderboard
29 Claude Haiku 4.5 14% AutoNudge Oct 2025 Official leaderboard
30 MiniMax-M2.7 13% baseline Mar 2026 Official leaderboard

The benchmark's own leaderboard has 9 models. Switch the scores above to rank them together.

The best score, 78%, costs $293 a task

Runs on the cost frontier score higher than any run that's cheaper. The costs are the leaderboard's own estimates, so compare them only within this benchmark.

Anthropic MiniMax Moonshot AI OpenAI Cost frontier One model at each effort level
0% 20% 40% 60% 80% 100% $0.10 $1.00 $10 $100 $1,000 Cost per task, log scale Claude Mythos Preview Claude Mythos Preview GPT-5.5 GPT-5.5 GPT-5.5 Kimi K2.6 Claude Haiku 4.5 0% 20% 40% 60% 80% 100% $0.10 $1.00 $10 $100 $1,000 Cost per task, log scale Claude Mythos Preview Claude Mythos Preview

Source: Official ExploitBench leaderboard

ModelEffortHarnessScoreCost per taskOutput tokens
Claude Mythos Preview AutoNudge 78% $293
Claude Mythos Preview baseline 72% $206
GPT-5.5 Codex, AutoNudge 72% $255
GPT-5.5 AutoNudge 47% $66
GPT-5.5 baseline 42% $15
GPT-5.5 Codex, baseline 33% $10
Claude Opus 4.7 AutoNudge 28% $46
Claude Sonnet 4.6 AutoNudge 26% $54
Gemini 3.1 Pro baseline 26% $28
Claude Sonnet 4.6 baseline 25% $35
Claude Opus 4.7 baseline 25% $29
GLM-5.1 AutoNudge 18% $7.27
Kimi K2.6 AutoNudge 18% $7.23
Gemini 3.1 Pro AutoNudge 16% $20
GLM-5.1 baseline 16% $6.50
Kimi K2.6 baseline 16% $5.42
Claude Haiku 4.5 AutoNudge 14% $2.74
Claude Haiku 4.5 baseline 14% $0.85
MiniMax-M2.7 baseline 13% $0.77
MiniMax-M2.7 AutoNudge 13% $1.63

4 models have held number one in labs’ own numbers since its release in May 2026 Number one over time 2 models have held number one with claims included since its release in May 2026

Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for the benchmark’s own leaderboard and what labs claim in their cards.

Anthropic OpenAI
Own leaderboard Not tested since May 2026
Lab claims Passed 85% in Sep 2026, by GPT-6 Astra

Sources: Official ExploitBench leaderboard and labs’ model cards

OpenAI’s own number for GPT-6 Astra passed 85% in September 2026

All the scores we have, one dot each, so a model tested at several settings appears more than once.

On the benchmark’s own leaderboard Reported by the lab in its model card Best so far
0% 20% 40% 60% 80% 100% 2026 2027 Near the ceiling (85%) GPT-6 Astra Claude Mythos Preview Claude Sonnet 4.6 Claude Haiku 4.5 0% 20% 40% 60% 80% 100% 2026 2027 Near the ceiling (85%) GPT-6 Astra Claude Mythos Preview

Sources: Official ExploitBench leaderboard and labs’ model cards

5 labs put it in a launch post in the last six months

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

OpenAI
Z.ai
Xiaomi Corp
Moonshot AI
Cognition
DateLaunch postScoreAs the post writes it
Nov 5, 2026 GPT-6 Cyber 100 ExploitBench, ACE-normalized mean capability score
Nov 4, 2026 SWE-2 Flash 34.8 ExploitBench
Oct 24, 2026 Kimi K3.1 Pro 74.7 ExploitBench (pass@5 max capability score, 300 turns)
Sep 22, 2026 MiMo-V2.6 Pro 47.9 ExploitBench
Aug 14, 2026 GLM-5.3 54.4 ExploitBench
Jul 9, 2026 GPT-5.6 Luna 33.2 ExploitBench
Jul 9, 2026 GPT-5.6 Terra 52.9 ExploitBench

26 system cards report it, from 6 labs

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
Nov 5, 2026 GPT-6 Cyber system card 100 ExploitBench, ACE-normalized mean capability score Cyber risk
Oct 29, 2026 GPT-6 Luna system card addendum 46.2 ExploitBench, maximum reasoning effort (8.1.2.1) Cyber risk
Oct 26, 2026 GPT-6.1 Terra system card addendum 97.1 ExploitBench, ACE-normalized mean capability score, max tested solution length (Figure 26, 9.0.2.1) Cyber risk
Oct 23, 2026 Muse Spark 1.3 system card 28.7 ExploitBench capability coverage with AutoNudge, Muse Spark 1.3 (max) (Table 1, Table 3). Mean capability score 4.16 Cyber risk
Oct 13, 2026 Gemini 4 Argon system card 87 ExploitBench, autonudge, 300-turn limit, best-of-three union, capabilities achieved 87% of 656 (7.1.1) Cyber risk
Oct 12, 2026 Muse Wonder Full model card 58.9 ExploitBench, Muse Wonder Full, metric not named (Cyber Capability Evaluations table, section 4) Cyber risk
Oct 7, 2026 GPT-6 Sol system card addendum 82.6 ExploitBench, maximum reasoning effort (8.1.2.1) Cyber risk
Oct 7, 2026 GPT-6 Luna system card addendum 44.7 ExploitBench, maximum reasoning effort (8.1.2.1) Cyber risk
Oct 7, 2026 Claude Haiku 5.5 system card 49 ExploitBench, Cap% in the AutoNudge arm shown in the figure (mean 6.56 flags). Plain arm Cap% 38 (mean 5.15 flags). Full ACE 4/410 runs (3.3.1, Figure 3.3.1.A) Cyber risk
Sep 29, 2026 GPT-6.1 Sol system card addendum 99.7 ExploitBench, maximum reasoning effort (9.1.2.1) Cyber risk
Sep 28, 2026 Claude Sonnet 5.5 system card 80 ExploitBench, AutoNudge arm Cap% 80%, mean 11.53 flags, full ACE in 178 of 410 runs (43.4%) (3.2.1, Figure 3.2.1.A) Cyber risk
Sep 22, 2026 MiMo-V2.6 Pro technical report 47.9 ExploitBench (Table 3) Cyber risk
Sep 22, 2026 GPT-6 Sol system card 81.7 ExploitBench, capability coverage at maximum reasoning effort (A.8.1.2.1, Figure 79) Cyber risk
Sep 22, 2026 GPT-6 Luna system card 43.4 ExploitBench, capability coverage at maximum reasoning effort (A.8.1.2.1, Figure 79) Cyber risk
Sep 22, 2026 Claude Opus 5.5 system card 91 ExploitBench, Cap% 91% in both the plain and AutoNudge arms (mean 13.99 flags plain, 14.15 AutoNudge), full ACE in 301 of 410 runs (73.4%), 41 V8 environments (3.3.1, Figure 3.3.1.A) Cyber risk
Sep 3, 2026 GPT-6 Astra system card 100 ExploitBench, Cap Percent, all reasoning efforts tested (10.1.2.1) Cyber risk
Jul 27, 2026 Kimi K3 technical report 32 ExploitBench, UK AISI and CAISI joint assessment cited in 6.2.2. Arbitrary code execution on 0 of 41 tasks Cyber risk
Jul 24, 2026 Claude Opus 5 system card 70 ExploitBench, AutoNudge Cap% 70 over 41 V8 environments, mean flags 10.14 AutoNudge and 9.62 plain, 99 full ACE exploits across both arms, production safety interventions off (3.3.1, Figure 3.3.1.A) Cyber risk
Jul 9, 2026 GPT-5.6 Terra system card ExploitBench, cap percent by output tokens, chart without printed numbers (Figure 33, 9.1.2.4.1) Cyber risk
Jul 9, 2026 GPT-5.6 Sol system card ExploitBench, cap percent by output tokens, chart without printed numbers (Figure 33, 9.1.2.4.1) Cyber risk
Jul 9, 2026 GPT-5.6 Luna system card ExploitBench, cap percent by output tokens, chart without printed numbers (Figure 33, 9.1.2.4.1) Cyber risk
Jun 30, 2026 Claude Sonnet 5 system card 31 ExploitBench, AutoNudge arm Cap% 31, mean 4.18 flags (plain arm mean 3.96), full ACE 0, 41 V8 environments, five trials (3.2.1, Figure 3.2.1.A) Cyber risk
Jun 25, 2026 GPT-5.6 Terra system card ExploitBench, cap percent by output tokens, chart without printed numbers (Figure 33, 9.1.2.4.1) Cyber risk
Jun 25, 2026 GPT-5.6 Sol system card ExploitBench, cap percent by output tokens, chart without printed numbers (Figure 33, 9.1.2.4.1) Cyber risk
Jun 25, 2026 GPT-5.6 Luna system card ExploitBench, cap percent by output tokens, chart without printed numbers (Figure 33, 9.1.2.4.1) Cyber risk
May 28, 2026 Claude Opus 4.8 system card 5.45 ExploitBench v2, mean capability flags out of 16 over three trials, AutoNudge arm, no safeguards (plain arm 5.02, plain arm with Tier-3 safeguards 0.46 on chart) (3.3.1, Figure 3.3.1.A) Cyber risk

More in Cybersecurity

All 115 in Cybersecurity
  • ExploitGym In use 869 real-vulnerability exploit-development tasks (userspace, V8, Linux kernel). Success means capturing a flag through the intended vulnerability. GPT-6 Astra 42.4%
  • CyberBench v1.1 (Vals) In use Agents work on OSS-Fuzz memory-safety bugs from ARVO images in two tracks. They write a proof-of-concept input that crashes the target, or patch the source so the crash stops and tests still pass. Muse Wonder 80.4%
  • SRE-Bench In use Software reverse engineering without source: 262 binary instances from 19 private programs, each with six graded objectives. GPT-6 Astra 56.9%
  • CyScenarioBench In use Scenario-based long-horizon security challenges in sandboxes, organized in task, scenario and campaign tiers. Evaluation set kept private. Gemini 4 Argon 100%
  • ExploitBench - Internal Port In use Agents develop working exploits for recently disclosed vulnerabilities to limit contamination. Scored as arbitrary code execution success rate. GPT-6 Cyber 42%
  • MiMo Cyber Bench In use Agents do in-house cybersecurity tasks that add to public vulnerability reproduction and exploitation benchmarks. The report gives no task count or grading details. MiMo-V2.6 Pro 81.7%