Cyber harm coverage (Anthropic)
Cyber safeguard classifiers screen examples from each cyber harm category. Score is overall recall, the share of harmful examples flagged.
Measures the deployed classifier system, not the model alone.
- Made by
- Anthropic
- Released
- July 2026
- Kind
- Refusing harmful requests
- Level
- Expert
- Scored
- Checked automatically
- Answers
- Short answer
- Tasks
- Kept private
- Strongest model tested
- Claude Fable 5.2 #1 on the capability index
- Last in a system card
- November 2026
- Last model added
- November 2026
Claude Fable 5.1 leads with 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.
- 1 Claude Fable 5.1 100%
- 2 Claude Fable 5.2 99.8%
- 3 Claude Opus 5.5 99.7%
- 4 Claude Opus 5 99.6%
- 5 Claude Sonnet 5.5 99.4%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Claude Fable 5.1 | 100% | Sep 2026 | Lab model card | |
| 2 | Claude Fable 5.2 | 99.8% | Nov 2026 | Lab model card | |
| 3 | Claude Opus 5.5 | 99.7% | Sep 2026 | Lab model card | |
| 4 | Claude Opus 5 | 99.6% | Jul 2026 | Lab model card | |
| 5 | Claude Sonnet 5.5 | 99.4% | Sep 2026 | Lab model card |
2 models have held number one in labs’ own numbers since its release in July 2026
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Labs’ model cards
Anthropic’s own number for Claude Opus 5 passed 85% in July 2026
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.
5 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 |
|---|---|---|---|---|
| Nov 9, 2026 | Claude Fable 5.2 system card | 99.8 | Cyber coverage evaluation, overall recall of deployed classifiers, 99.8% printed on chart (Figure 3.4.1.A) | Cyber risk |
| Sep 28, 2026 | Claude Sonnet 5.5 system card | 99.4 | Cyber coverage evaluation, overall recall of the safeguard classifiers (3.3.1, Figure 3.3.1.A) | Cyber risk |
| Sep 22, 2026 | Claude Opus 5.5 system card | 99.7 | Cyber coverage evaluation, overall recall of Opus 5.5's deployed classifiers, printed on chart (3.4.1, Figure 3.4.1.A) | Cyber risk |
| Sep 1, 2026 | Claude Fable 5.1 system card | 100 | Cyber coverage evaluation, overall recall of Fable 5.1's deployed classifiers, 100.00% printed on chart (Figure 3.4.1.A, 3.4.1) | Cyber risk |
| Jul 24, 2026 | Claude Opus 5 system card | 99.6 | Cyber coverage evaluation, overall recall of Opus 5's deployed classifiers, printed on chart (3.4.3, Figure 3.4.3.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%