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DeepSeek

DeepSeek R1-0528

Published evidence on capabilities, behavioral tendencies and observed actions.

First public availability
2025-05-28
Parameters
Not yet verified
Metadata updated
2026-10-27
Sources ↓

Evidence overview

Published risk evidence is organized by assessment and protocol. Missing evidence is not a low-risk finding.

NUWA curates and interprets these sources. Experiments are attributed to their original executors; this page does not claim NUWA has independently replicated them.

MODEL MONITORING

Representative benchmark coverage

Results by protocol and configuration; gaps show records awaiting collection or linkage.

CyberGym →

No eligible measurement linked to this model version.

MASK →

No eligible measurement linked to this model version.

All linked measurements

Each result retains its protocol and unit.

4 observations

Measurements and source conditions
System / modelResultCondition statusTask / conditionsEvaluator / reportDates
DeepSeek R1-052837%AgentDojo · Hijacking attempted-task frequencyIncompleteAgentDojo Workspace; Credential exfiltrationHijacking attempted-task frequency—NIST / CAISIEvaluation of DeepSeek AI ModelsRelease 2025-05-28Report 2025-09-30
DeepSeek R1-052848%AgentDojo · Hijacking attempted-task frequencyIncompleteAgentDojo Workspace; Phishing emailHijacking attempted-task frequency—NIST / CAISIEvaluation of DeepSeek AI ModelsRelease 2025-05-28Report 2025-09-30
DeepSeek R1-052849%AgentDojo · Hijacking attempted-task frequencyIncompleteAgentDojo Workspace; Download/run malwareHijacking attempted-task frequency—NIST / CAISIEvaluation of DeepSeek AI ModelsRelease 2025-05-28Report 2025-09-30
DeepSeek R1-052835.5%Cybench · Reported benchmark performanceIncompleteCybenchReported benchmark performance500,000 weighted tokens per agentic task (Appendix A2)CAISI ReAct-style agent; InspectNIST / CAISIEvaluation of DeepSeek AI ModelsRelease 2025-05-28Report 2025-09-30

Developer disclosures

No developer-authored safety report has been linked to this exact model record in the current collection.

External assessments

NIST / CAISI

Evaluation of DeepSeek AI Models →

Reported differences depend on task, scaffold and scoring; institutional judgments are retained as source judgments rather than NUWA findings.

2025-09-30

Evidence by risk topic

Autonomy No structured result linked

A gap in this collection is not evidence of low risk. Consult the linked reports for unextracted findings and protocol scope.

Deception No structured result linked

A gap in this collection is not evidence of low risk. Consult the linked reports for unextracted findings and protocol scope.

Cybersecurity 4 protocol results

Cybench →

External evaluation · Executed by NIST / CAISI

Reported benchmark performance
35.5%

Source denominator: 40 (unit not disclosed)

Agent hijacking →

External evaluation · Executed by NIST / CAISI

Hijacking attempted-task frequency
37%

Per-result sample size not disclosed

Agent hijacking →

External evaluation · Executed by NIST / CAISI

Hijacking attempted-task frequency
48%

Per-result sample size not disclosed

Agent hijacking →

External evaluation · Executed by NIST / CAISI

Hijacking attempted-task frequency
49%

Per-result sample size not disclosed

CBRN No structured result linked

A gap in this collection is not evidence of low risk. Consult the linked reports for unextracted findings and protocol scope.

Disinformation No structured result linked

A gap in this collection is not evidence of low risk. Consult the linked reports for unextracted findings and protocol scope.

Autonomous physical harm No structured result linked

A gap in this collection is not evidence of low risk. Consult the linked reports for unextracted findings and protocol scope.

Source review and evidence gaps

Evaluation of DeepSeek AI Models →

Source-specific extraction of CAISI · DeepSeek models. Findings and measurements retain their original attribution.

Source transcription is not experimental replication. Unknown dates, evaluator roles and configuration details remain unknown. Source groups are not verified rankings.

Missing scores may reflect unextracted sections, undisclosed configurations, unresolved identity or an absent experiment. These are separate research questions; none implies a zero result.

Interpretation and open questions

Differences between reports can reflect task selection, model endpoints, prompts, budgets, judges and publication dates. Evidence is grouped by the protocol actually used; no model-wide safety grade is inferred.

References

  1. [1] deepseek-r1-0528 release ; News article title, dated heading and availability
  2. [2] Evaluation of DeepSeek AI Models. 2025-09-30. 30 September 2025 ; p. 24, Table 4.1, row Cybench, column DeepSeek R1-0528; p. 17, key findings, Credential exfiltration; p. 17, key findings, Phishing email