Cisco Introduces Privacy-First AI Models for Secure Software Code Analysis

Cisco has introduced Antares, a family of small language AI models (SLMs) purpose-built to tackle one of the most difficult and time-consuming challenges in cybersecurity: finding hidden security flaws within software codebases, on-premises, without externalizing organizations’ data.

As organizations race to secure their digital infrastructure, finding vulnerabilities quickly is critical. However, using general-purpose AI to scan code can be expensive and often requires sending sensitive, proprietary source code to the cloud, representing a major hurdle for organizations with strict privacy and compliance requirements.

To help address this, Cisco has introduced Antares. These models are compact, cost-effective, and capable of running locally within an organization’s own secure environment.

“As regional organizations accelerate their digital capabilities, securing complex software without compromising data privacy is critical and urgent. With Antares, we are giving security teams the power of AI locally so they can pinpoint vulnerabilities faster while keeping sensitive source code firmly within their own secure environment.”

– Fady Younes, Managing Director for Cybersecurity, Cisco Middle East, Türkiye, Africa, Caucasus and Central Asia (METAC)

Cisco is releasing two of these models (Antares-350M and Antares-1B) entirely openly to the broader developer and security community.

Key highlights of the Antares launch include:

• Privacy-First Security: Because the models are compact enough to run locally, security teams do not need to send sensitive source code to the cloud. This makes Antares ideal for the public sector, universities, and organizations with strict data sovereignty rules.
• Unmatched Efficiency: Benchmark testing shows that the Antares models outperform many larger, more expensive AI models in critical security tasks, operating at a fraction of the cost.
• Human-Like Investigation: Rather than relying on rigid rules, Antares reads vulnerability descriptions, searches for relevant code, changes direction if a path is unhelpful, and narrows down the file paths most likely to contain a threat.
• Democratizing AI Security: By making these tools openly available, Cisco is unlocking the power of AI-assisted security for smaller teams that previously lacked the access, budget or resources to deploy proprietary large language AI models.

With the release of Antares, Cisco is moving beyond simply building models; it is helping create the ecosystem and standards needed for practical, trustworthy enterprise AI adoption.

For more technical detail on the Antares family of AI models, and to potentially access Cisco’s new open-weight models, see the official global announcement here.