Secure and defensive coding (Anthropic)
Cyber safeguard classifiers screen sampled defensive coding sessions such as patching and incident response. Score is the classifier flag rate.
Measures false positives of the deployed classifier system on benign cyber work. An LLM grader labels sessions as purely defensive.
- Made by
- Anthropic
- Released
- July 2026
- Kind
- Refusing harmful requests
- Level
- Expert
- Scored
- Graded by a model
- Answers
- Open-ended
- Tasks
- Kept private
- Strongest model tested
- Claude Fable 5.1 #7 on the capability index
- Last in a system card
- September 2026
- Last model added
- September 2026
Claude Opus 5 leads with 0.61%
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.
- 1 Claude Opus 5 0.61%
- 2 Claude Fable 5.1 1.03%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Claude Opus 5 | 0.61% | Jul 2026 | Lab model card | |
| 2 | Claude Fable 5.1 | 1.03% | Sep 2026 | Lab model card |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
Labs report it only in system cards
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark. Some system cards do, below.
2 system cards report it, from 1 lab
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.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Sep 1, 2026 | Claude Fable 5.1 system card | 1.03 | Production secure coding sessions, classifier flag rate, lower is better (Figure 3.4.3.A, 3.4.3) | Cyber risk |
| Jul 24, 2026 | Claude Opus 5 system card | 0.61 | Production secure coding sessions, classifier flag rate, lower is better, printed on chart (3.4.2, Figure 3.4.2.A) | Cyber risk |
More in Safety and alignment
- FORTRESS In use Paired adversarial and benign national-security misuse prompts. Rubric-graded risk score on adversarial and over-refusal score on benign prompts. Claude Opus 5.5 5.78%
- StrongREJECT In use Forbidden-prompt jailbreak benchmark with a rubric grader that scores how useful a non-refusal actually is.
Inkling 98.6% - Gray Swan IPI Arena benchmark In use Indirect prompt-injection attacks from public red-teaming competitions replayed on tool, coding and browser agents. Attack success rate at k attempts.
Gemini 4 Carbon 0% - DistressBench In use Models reply as a chatbot to 718 simulated users in psychological crisis, in single-turn and multi-turn chats. Three judge models score replies against clinician-written rubrics.
Muse Spark 1.2 88.4% - Lakera B3 (Backbone Breaker Benchmark) In use Crowdsourced prompt-injection attacks hit backbone LLMs inside agent threat snapshots at three defense levels. The score is attack resistance, 100 minus the board's vulnerability percentage. Claude Opus 4.5 89%
- IHEval In use Models face conflicts between system, user and tool instructions. Reports a composite score for following the higher-priority instruction. GPT-4o 70%