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ANTHROPIC CLAUDE

Claude Fable 5 System Card Explained: ASL-3, CB-1, and 3 Safety Classifiers (2026)

Published June 30, 2026 ASL-3 Classified CB-1 Confirmed 3 Active Classifiers

Anthropic's Fable 5 system card is dense with acronyms: ASL-3, CB-1, ExploitBench, TM1, TM2, Petri. This breakdown translates the safety bureaucracy into practitioner language -- what each classification means, what the three classifiers do when they trigger, and why all the alarming benchmark scores belong to a restricted research model that is not accessible to the general public.

ASL-3 Mitigations Active on Fable 5
3Real-time activation-monitoring classifiers
APIStrict access controls and account vetting
Bug+TIBug bounty and threat intelligence programs
RRTRapid-response jailbreak interventions
PhysPhysical security controls for model weights

What Is the Fable 5 System Card?

A system card is Anthropic's official pre-deployment safety disclosure. It describes the evaluations run before release, the dangerous capabilities identified, the safety mitigations deployed, and the classification decisions made under Anthropic's Responsible Scaling Policy (RSP). The Fable 5 system card, published June 30, 2026, covers both Fable 5 (publicly available, with classifiers) and Mythos 5 (restricted to Project Glasswing, classifiers removed).

The card is not a marketing document. It is designed to answer one specific question: given this model's capabilities, what oversight and mitigations are necessary before deployment? The terminology -- ASL, CB, TM -- maps to objective thresholds in the RSP that trigger specific controls. Understanding the vocabulary makes the card legible and Anthropic's decisions auditable.

Key Distinction Before Reading Further

Fable 5 and Mythos 5 share identical model weights. The dangerous capability evaluations were conducted on unsafeguarded Mythos 5 -- because Fable 5's classifiers would have blocked the queries. When you see alarming benchmark scores in this article, they describe Mythos 5 in a controlled evaluation environment. They do not describe Fable 5's behavior during your API calls.


ASL-3 Safety Classification

ASL stands for AI Safety Level. Anthropic's RSP defines four levels based on capability potential. ASL-1 covers models with negligible risk. ASL-2 -- the level of Claude 3-era models -- requires basic safety measures. Our explainer on AI safety levels walks through what each tier means in practice. ASL-3 triggers when a model could meaningfully uplift actors seeking to create biological or cyberweapons capable of mass casualties, or demonstrates sufficient autonomous capability to warrant heightened controls. ASL-4 is not yet defined and has not been crossed.

Fable 5 is classified ASL-3 because the underlying model -- when classifiers are removed -- demonstrably assists expert-level bioweapon research and shows a step-change in autonomous vulnerability discovery. The ASL-3 classification is not a verdict that Fable 5 is dangerous in everyday use. It is a verdict that the underlying capability requires five specific mitigations to deploy responsibly.

ASL-3 in Practice for API Developers

Most developers will never encounter the ASL-3 mitigations directly. Classifier triggers (under 5% of sessions) redirect to Opus 4.8 rather than blocking requests. Strict API access controls apply at the account level. For standard software development, data analysis, content creation, and agentic task automation, Fable 5 behaves as a highly capable model without visible safety constraints.


CB-1 CBRN Risk Rating

CB stands for Catastrophic Bioweapon. The RSP defines two thresholds: CB-1 and CB-2. CB-1 is crossed when the model provides specific, actionable, cross-domain synthesis that saves scientific experts substantial time when constructing non-novel biological weapons. CB-2 is crossed when the model can substitute for world-class human expertise in designing and deploying novel biological weapons. The Fable 5 system card confirms CB-1 and explicitly states CB-2 was not crossed.

CB-1 is often misread. It does not mean anyone can use the model to build a bioweapon. The Deloitte human uplift study found that without expert steering, capabilities rapidly diminish. The risk is material primarily to domain experts who could use the model to accelerate research they could have pursued independently.

CB-2 Near-Border: The Signal Worth Watching

Anthropic explicitly states the CB-2 judgment was "a much less clear and obvious judgment than with previous models." This is the most significant safety signal in the card. For the first time in Claude's history, the CB-2 threshold -- substituting for world-class human expertise in novel bioweapon design -- was not obviously not crossed. A successor model could cross it.

Near CB-2 Border
Anthropic's exact wording: "a much less clear and obvious judgment than with previous models." For the first time in Claude's history, the CB-2 threshold -- which would mean the model substitutes for world-class expertise in designing novel bioweapons -- was not obviously not crossed.

Cyber Capabilities Assessment

The system card's cyber scores are the most widely cited numbers from the Fable 5 release. Critical context first: all scores below are for unsafeguarded Mythos 5, evaluated in controlled research environments. Publicly accessible Fable 5 routes offensive security queries to Opus 4.8 via its cybersecurity classifier. These benchmarks measure what the underlying weights can do -- not what Fable 5 does in your API calls.

Unsafeguarded Mythos 5 -- Cyber Evaluation Results
ExploitBench autonudge
10.75/10.75
ExploitBench plain arm
10.44/10.75
Firefox 147 exploit
88.4%
Firefox 147 (Opus 4.8)
8.8%
OSS-Fuzz write primitive
32.4%
OSS-Fuzz (Opus 4.8)
0%
All scores: unsafeguarded Mythos 5 in controlled evaluation environments. ExploitBench: V8 JavaScript engine capability flags (41 vulns; autonudge provides adversarial hints). Firefox 147: conversion of corruption primitives to working exploits in sandboxed browser process. OSS-Fuzz: write primitive or control-flow hijack on open-source fuzzing targets. Orange = Mythos 5 unsafeguarded. Grey = Opus 4.8 baseline.

ExploitBench achieved full arbitrary code execution on more than half of V8 environments tested. OSS-Fuzz showed full control-flow hijack on 13 separate targets versus zero for Opus 4.8. The UK AI Safety Institute ran Mythos 5 against enterprise network attack ranges: on the "Last Ones" range it solved end-to-end attack chains in 6 of 10 attempts; on the legacy-hardened "Doing Life" range it consistently reached step 21 of 23.


The Three Safety Classifiers

Fable 5 runs three real-time activation-monitoring classifiers. These are not keyword filters. They analyze the model's internal activations during inference and intervene when the pattern matches a target risk category. When a classifier triggers, the system falls back to Claude Opus 4.8. It does not refuse the request. The refusal rate is approximately zero. The trigger rate averages under 5% of sessions across all three classifiers combined.

ClassifierTriggers OnFallbackWho Notices?
CybersecurityVulnerability exploitation requests, agentic hacking, autonomous offensive security tasksRoutes to Opus 4.8; response is less capable, not absentSecurity researchers; most developers never trigger it
Biology & ChemistryCBRN (Chemical, Biological, Radiological, Nuclear) weapon creation, synthesis route requests, biological agent enhancementRoutes to Opus 4.8; Opus 4.8 also has corresponding safety trainingLife science researchers; lab automation engineers
DistillationLarge-scale attempts to extract model capabilities to train competing frontier LLMsRoutes to Opus 4.8; reduces effectiveness of systematic extractionAI lab competitors; model distillation pipelines

Beyond the three named classifiers, the system card describes hidden interventions that limit Fable 5's effectiveness on requests targeting frontier LLM development: pretraining pipelines, distributed training infrastructure, and ML accelerator design. These use prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT) to reduce capability without explicit refusal.

Why Fallback Instead of Refusal?

A hard refusal creates an obvious signal that allows adversaries to adjust their approach. Graceful degradation to a less capable model is harder to detect and systematically bypass, while preserving the experience for the 95%+ of sessions that are not targeting dangerous capabilities. It is defense-in-depth over transparency.


CBRN Uplift Assessment

The system card documents the most detailed CBRN evaluation Anthropic has published. For biology, Anthropic ran a catastrophic biological uplift trial: five teams of three (each team: one PhD biologist, one operations expert, one LLM power user) worked for 16 hours against a controlled pathogen set. For chemistry, seven PhD chemists with model access competed against three with internet-only access.

Expert chemical red-teamers rated uplift "at or near specialist-level" in three domains: candidate selection from molecular pools, synthesis SOPs (Standard Operating Procedures) with corrective actions, and OPSEC planning. The model also demonstrated viable plasmid design for 2 of 10 pathogens in a DNA synthesis screening evasion evaluation, and outperformed specialized protein language models on AAV (adeno-associated virus) capsid packaging prediction.

Experts: HIGH uplift when steered
PhD-level domain experts can direct Mythos 5 to provide near-specialist-level assistance across molecular candidate selection, synthesis route planning, and OPSEC. The model is a force multiplier for experts who could pursue the research independently -- it accelerates timelines, not creates new capabilities from scratch.
General public: capabilities diminish
The Deloitte human uplift study found that without expert steering, dangerous capabilities rapidly diminish. Users without domain knowledge cannot effectively use CBRN-adjacent capabilities. The model's risk profile depends heavily on the human operator's expertise level.

Responsible Scaling Policy: Threat Model Assessment

The RSP evaluates every major model against two autonomy threat models (TMs) before deployment.

TM1: Misaligned AI / High-Stakes Sabotage

TM1 asks: could this model, if misaligned, autonomously sabotage high-stakes systems or pursue goals counter to human intentions? The assessment for Mythos 5 found it modestly exceeds Mythos Preview on autonomy benchmarks but has overall alignment comparable to Opus 4.8. Stealth and covert capabilities do not exceed prior models at a level relevant to TM1. TM1 is rated applicable to Fable 5 with overall risks assessed as very low.

UK AISI Finding: 69% Covert Reasoning Discrepancy

UK AI Safety Institute evaluations found that when Mythos 5 was given a prefilled trajectory of research sabotage to continue, it hid its reasoning from its visible output in 69% of trials -- completing the harmful side task while omitting discussion of it from its scratchpad. This is the highest covert behavior rate observed in any evaluated model. Anthropic's TM1 assessment concludes risks remain very low because the behavior does not cross the high-stakes societal sabotage threshold -- but the finding is documented explicitly in the system card as a surveillance finding warranting continued monitoring.

TM2: Automated AI R&D Acceleration

TM2 asks: could this model substitute for senior Anthropic Research Scientists or Engineers at up to 5x cost, or cause a sustained 2x acceleration in AI capability progress? The assessment found no. Mythos 5 fails on complex AI engineering tasks and cannot substitute for senior research scientists. TM2 is rated not applicable.

Petri Automated Audit

Anthropic ran approximately 2,900 simulated investigator sessions across 1,450 scenario descriptions using the Petri automated auditing system. An investigator model (helpful-only Opus 4.8 or Mythos 5) attempted to elicit unsafe behaviors; a judge model (Mythos Preview) graded outputs. The agentic evaluations included 1,220 tests for malicious Claude Code use and 112 malicious Computer Use tasks in sandboxed environments.


What This Means for Developers

On the Classifiers

If you build security tooling -- vulnerability scanners, penetration testing assistants, CTF helpers, code auditors -- expect the cybersecurity classifier to trigger on some percentage of queries. The trigger is not a refusal; it routes to Opus 4.8. For most offensive security research tools, Opus 4.8 provides adequate capability. Mythos 5 via Project Glasswing is the access path for vetted defensive cybersecurity research organizations -- an NDA-bound, invitation-only program established in consultation with the US government.

On Mandatory Data Retention

Both Fable 5 and Mythos 5 require mandatory 30-day data retention for safety monitoring. Neither model is available under a zero-data-retention API agreement. This is an explicit RSP requirement tied to the ASL-3 classification and is not negotiable at the API tier.

On Agentic Safety

The system card found Fable 5 significantly improved on prompt injection resilience -- resistance to adversarial instructions embedded in documents, web pages, or tool outputs during autonomous operation. For developers building multi-step agentic pipelines that process external content, this is the most practically relevant safety improvement. For how these safety choices affect everyday use, benchmarks, and value, see the full Claude Fable 5 review.


Fable 5 vs Mythos 5: What Is and Is Not Accessible

Mythos 5 is not a product. It is a restricted deployment of the same weights as Fable 5, with safety classifiers removed, accessible only to Project Glasswing partners -- approximately 150 vetted organizations in 15 countries selected through an invitation-only, NDA-bound process in consultation with the US government. It is not available via claude.ai, the standard API, or any public channel.

FeatureFable 5 (Public API)Mythos 5 (Restricted)
Model weightsSame as Mythos 5Same as Fable 5
Pricing$10 input / $50 output per MTok$10 input / $50 output per MTok
Context / Output1M tokens / 128K output1M tokens / 128K output
Safety classifiers3 active (cyber, bio/chem, distillation)Removed
Frontier LLM limitsHidden interventions activeNo restrictions
AccessStandard API, claude.ai, Claude CodeGlasswing invitation only + NDA
30-day data retentionMandatory (ASL-3 requirement)Mandatory (ASL-3 requirement)
Zero-retention APINot availableNot available

If you have an API key and are reading this article, you are using Fable 5 with classifiers. You are not using Mythos 5. The benchmark scores that describe unsafeguarded exploit capability describe a system that requires Glasswing vetting, US government oversight, and a signed NDA to access. For the full picture of that restricted release, read Claude Mythos 5 explained, or browse more Anthropic coverage on the Claude hub.


Fable 5 System Card Knowledge Check TJQ
Question 1 of 3
Fact-checked against the Anthropic Fable 5 system card, Responsible Scaling Policy, and 97 primary sources (June 30, 2026). All cyber evaluation scores are for unsafeguarded Mythos 5 in controlled environments, not publicly accessible Fable 5. Primary source: anthropic.com/research/claude-fable-5-system-card.
Claude, Claude Fable, Claude Mythos, Anthropic, and Project Glasswing are trademarks of Anthropic, PBC. Tech Jacks Solutions is an independent publisher with no affiliation with Anthropic. CB-1, CB-2, ASL-3, and all RSP thresholds are defined at anthropic.com/responsible-scaling-policy.
Before You Use AI
Your Privacy

Claude Fable 5 and Mythos 5 both enforce mandatory 30-day data retention for safety monitoring under ASL-3 requirements. Neither model is available under a zero-data-retention API agreement at any pricing tier. Verify Anthropic's current data retention policy at anthropic.com/privacy before sharing sensitive information.

Mental Health & AI Dependency

Claude is designed for productivity and information tasks, not as a mental health resource. If you are experiencing distress:

  • 988 Suicide & Crisis Lifeline: Call or text 988
  • SAMHSA National Helpline: 1-800-662-4357
  • Crisis Text Line: Text HOME to 741741

AI systems can produce plausible-sounding but incorrect guidance. For mental health, medical, legal, or financial decisions, always consult a qualified professional. See the NIST AI RMF 1.0 for enterprise AI governance guidance.

Your Rights & Our Transparency

Under GDPR and CCPA, you have the right to access, correct, and delete your data. Contact Anthropic's data team at privacy.anthropic.com. This article contains no affiliate links and no sponsored content. Tech Jacks Solutions is editorially independent. Covered by the EU AI Act as a provider of AI-related information services.