Cisco AI Defense to Add Anthropic’s Claude Mythos for AI Red Teaming
By Google News AI ·
Cisco Blogs Artificial Intelligence - AI
For several years now, Cisco has pioneered the AI security industry with a number of firsts. It started with the launch of AI Defense, the first enterprise AI security offering to combine asset visibility, supply chain scanning, algorithmic red teaming, and runtime guardrails in a single unified solution.
When agents emerged and rapidly reframed the security conversation, we were the first to introduce adaptive red teaming and adaptive guardrail capabilities, enabling our customers to test for and protect against risks unique to their applications, organizations, and industries.
Today, we are extending that work. Cisco AI Defense is among the first AI security products to augment its adaptive AI red teaming framework with Anthropic’s Claude Mythos. We built an adaptive AI red teaming offering that pairs frontier attacker reasoning with responsible controls: authorization to test only targets the customer is permitted to test; attribution to a named operator; and full auditability.
Red team engagements should reflect adversary capability without compromising the security and safety of our customer environments.
This comes at a consequential moment, as businesses are eager to adopt agentic technologies and security teams work to keep pace. Beyond accounting for model behavior, organizations must now account for how agents behave once connected to a complex, interconnected system of tools, skills, and sensitive resources.
Every environment is different, and security teams need a way to find the risks specific to their own deployments before attackers do.
Since the launch of AI Defense, Cisco customers have leveraged its best-in-class red teaming capabilities to uncover critical safety and security vulnerabilities in their AI systems. By bringing Claude Mythos to AI Defense, we’re augmenting that system to deliver an advanced AI red teaming experience to customers.
To contextualize the impact of Claude Mythos, it’s important to first understand how Cisco AI Defense performs red team testing on agents and AI applications today.
AI Defense offers two types of red team testing: standard and adaptive.
Standard red teaming assesses AI systems for a wide range of common vulnerabilities. These are risks that virtually any agent or AI application would be susceptible to: prompt injection and jailbreaks, sensitive data exposure, and harmful content generation, for example. These standard tests cover thousands of different categories, content types, and adversarial techniques in minutes.
Results are detailed in a comprehensive report that maps back to Cisco’s Integrated AI Security and Safety Framework along with standards from OWASP, MITRE, and NIST.
Standard red teaming cannot comprehensively test for the specific risks unique to a given organization’s application, which is why we developed and launched our industry-defining adaptive red teaming agentic framework in AI Defense.
Users simply define custom testing criteria in plain language; our red teaming framework analyzes the target system, develops and tests attacks tailored to those criteria, and uses the target’s responses to refine its approach or change tactics. It then evaluates the results and furnishes a report of findings.
AI Defense recommends follow-up actions while also enabling customers to protect against specific risks by building custom adaptive guardrails in Policy Studio.
Cisco customers exist across virtually every industry…
Originally published by Google News AI
