Content safety classifiers
Separate models screen requests and responses at run time. |
AI used to run a cyber attack · Harmful content and jailbreaks · Weapons uplift (CBRN) · Manipulation and misinformation |
not seen in an incident yet |
Safety training and refusal
The model is trained to decline forbidden requests. |
AI used to run a cyber attack · Harmful content and jailbreaks · Weapons uplift (CBRN) |
did not hold in 2
held in 1 |
Cyber and weapons safeguards
Protections built for cyber offence and CBRN misuse. |
AI used to run a cyber attack · Weapons uplift (CBRN) |
not seen in an incident yet |
Dangerous-capability testing before release
The model is tested for cyber, CBRN and autonomy risk before release. |
AI used to run a cyber attack · Weapons uplift (CBRN) · AI R&D acceleration |
not seen in an incident yet |
Outside red-teaming
Independent testers attack the model before release. |
AI used to run a cyber attack · Harmful content and jailbreaks · Weapons uplift (CBRN) |
not seen in an incident yet |
Staged or restricted release
Access widens in steps or goes to vetted users first. |
AI used to run a cyber attack · Weapons uplift (CBRN) · AI R&D acceleration |
not seen in an incident yet |
Protection of model weights
Weights are guarded against theft and leaks. |
no risk linked |
not seen in an incident yet |
Abuse monitoring and account enforcement
The provider watches use and bans accounts that break policy. |
AI used to run a cyber attack · Harmful content and jailbreaks · Manipulation and misinformation |
not seen in an incident yet |
Reasoning monitoring
The model's intermediate reasoning is read for signs of misbehaviour. |
AI used to run a cyber attack · Deception, concealment or sabotage · Gaming the task (reward hacking) · Agents coordinating against their limits |
did not hold in 2 |
Safeguards kept on in testing
Production classifiers and refusals stay on in evaluations with real access. |
AI used to run a cyber attack |
did not hold in 2 |
Realistic behaviour evaluations
The model is tested in settings like real use for deception and cheating. |
Deception, concealment or sabotage · Gaming the task (reward hacking) · AI R&D acceleration |
not seen in an incident yet |
Flaw reporting and bug bounty
Outsiders can report flaws, with rewards or protection. |
no risk linked |
not seen in an incident yet |
Marking machine-made output
Generated content is labelled or watermarked. |
Copyright and IP · Manipulation and misinformation |
not seen in an incident yet |
Copyright safeguards
Output is screened for protected material. |
Copyright and IP |
not seen in an incident yet |