SusVibes
Coding agents rebuild a feature in a real open-source Python project from a plain-language request. Each task comes from a historical vulnerability fix, so the original human version was insecure. Hidden functional tests and security tests check the result. Scores report the share of solutions that work and the share that are also secure.
Endor Labs runs it as the Agent Security League, a public board of agent harness and model pairs (Claude Code, Codex, Cursor, SWE-agent). Endor added an anti-cheating check because some agents read the git history to recover the original fix. The paper and Endor describe 200 tasks across 77 CWE types, while the repository README now lists 186. The repository has about 57 GitHub stars and names ICML 2026 as the venue.
- Released
- December 2025
- Kind
- Secure code and review
- Level
- Expert
- Scored
- Checked automatically
- Answers
- Code
- Tasks
- All public
- Strongest model tested
- GPT-5.5 #20 on the capability index
- Last model added
- May 2026
- Scores refreshed
- November 12th, 2026
In the authors’ words
Vibe coding is a new software development paradigm in which human engineers prompt a large language model (LLM) agent to complete complex coding tasks with little supervision. Although vibe coding is increasingly adopted, is the generated code really safe to deploy in production? To investigate this question, we propose SUSVIBES, a benchmark consisting of 186 feature-request software engineering tasks from real-world open-source projects, for which, human programmers committed vulnerable implementations. We evaluate 12 widely used coding agentic settings with frontier models on the benchmark. Disturbingly, all agents perform poorly in terms of software security. Although 57% of the solutions from SWE-Agent with Claude 4 Sonnet are functionally correct, only 11.8% are secure. Further experiments demonstrate that preliminary security strategies, such as augmenting the feature request with vulnerability hints, cannot mitigate these security issues. Our findings raise serious concerns about the widespread adoption of vibe coding, particularly in security-sensitive applications. The code and dataset are available at https://github.com/LeiLiLab/susvibes. The leaderboard is at https://leililab.github.io/susvibes-leaderboard.
GPT-5.5 leads with 43.5% among models released by May 2026
Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.
The newest model with a score here came out in May 2026, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon
- GPT-6 Astra
- Claude Opus 5.5
- and 15 more
- 1 GPT-5.5 default 43.5%
- 2 MAI Code 1 Flash Internal default 42.5%
- 3 Claude Opus 4.8 default 32.8%
- 4 MiniMax M3 (MXFP8) default 26.3%
- 5
MiniMax-M2.7 default 18.8%
- 6
Qwen3.5-35B-A3B default 18.3%
- 7 GLM-5 default 14%
- 8
Gemini 3 Pro default 12.9%
- 9 Claude Sonnet 4 default 11.8%
- 10 glm-4.7-flash default 9.70%
- 11 Kimi K2 Sep 2025, default 9.10%
- 12 Gemini 2.5 Pro (snapshot unspecified) default 8.10%
- 13
Qwen3-Coder-Next default 7.50%
Source: Official SusVibes leaderboard
| # | Entry | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.5 | 43.5% | default, mini-SWE-agent | Apr 2026 | Official leaderboard |
| 2 | MAI Code 1 Flash Internal | 42.5% | default, mini-SWE-agent | Aug 2026 | Official leaderboard |
| 3 | Claude Opus 4.8 | 32.8% | default, Claude Code | May 2026 | Official leaderboard |
| 4 | MiniMax M3 (MXFP8) | 26.3% | default, mini-SWE-agent | Aug 2026 | Official leaderboard |
| 5 | | 18.8% | default, mini-SWE-agent | Mar 2026 | Official leaderboard |
| 6 | | 18.3% | default, mini-SWE-agent | Feb 2026 | Official leaderboard |
| 7 | GLM-5 | 14% | default, SWE-agent | Feb 2026 | Official leaderboard |
| 8 | | 12.9% | default, SWE-agent | Nov 2025 | Official leaderboard |
| 9 | Claude Sonnet 4 | 11.8% | default, OpenHands | May 2025 | Official leaderboard |
| 10 | glm-4.7-flash | 9.70% | default, SWE-agent | Jan 2026 | Official leaderboard |
| 11 | Kimi K2 Sep 2025 | 9.10% | default, OpenHands | Sep 2025 | Official leaderboard |
| 12 | Gemini 2.5 Pro (snapshot unspecified) | 8.10% | default, OpenHands | Dec 2025 | Official leaderboard |
| 13 | | 7.50% | default, SWE-agent | Feb 2026 | Official leaderboard |
5 models have held number one on the official leaderboard since its release in December 2025
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Official SusVibes leaderboard
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Official SusVibes leaderboard
No lab model card reports it yet
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.
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