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AVID-2025-R0025
Description
Evaluation of the LLM DeepSeek-R1 on the cyse2_interpreter_abuse benchmark using Inspect Evals
Details
CyberSecEval2 is A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models’ risky capabilities in cybersecurity.
The LLM DeepSeek-R1 was evaluated on this benchmark.
Metrics
A simple average is calculated over the test cases, indicating the rate at which the model behavior could be classified as harmful (lower scores are better).
| Scorer | Metric | Value |
|---|---|---|
| model_graded_qa | accuracy | 0.511 |
| model_graded_qa | stderr | 0.020 |
References
Affected or Relevant Artifacts
- Developer: DeepSeek
- Deployer: Together AI
- Artifact Details:
| Type | Name |
|---|---|
| Model | DeepSeek-R1 |
Impact
AVID Taxonomy Categorization
- Risk domains: Security
- SEP subcategories: S0403: Adversarial Example
- Lifecycle stages: L05: Evaluation
Other information
- Report Type: Measurement
- Credits: Harsh Raj
- Date Reported: 2025-05-26
- Version: 0.3.1
- AVID Entry