THE COMPANY INDEX TRACKED BLOG
Ideas, decisions, and lessons from the team.
snyk.io (opens on the source site)LinkedIn XStatic analysis found the flaws, but only live attack testing proved how they could be chained into breaches. A comparison of Evo COS, Claude Security, and Claude Code Security.
Read at the sourceAutonomous attackers are shrinking the window for defense. Learn how continuous discovery, remediation, validation, and prevention can help security teams keep pace.
Read at the sourceAI coding agents can produce authorization logic that compiles and passes review while exposing one tenant’s data to another. Learn why broken access control is difficult to detect and how to prevent it.
Read at the sourceEvo ADS Govern Agent Behavior is now generally available, starting with MCP Governance. Discover, approve, monitor, log, and block MCP server usage across leading AI coding agents.
Read at the sourceLearn how Agentic AppSec uses grounded, bounded, and independently verified AI agents to run the application security loop.
Read at the sourceA growing vulnerability backlog is more than technical debt: it is an attack surface. Learn why outdated risk assumptions, automated attackers, and chained findings demand a new approach.
Read at the sourceAI is accelerating software creation and cyberattacks alike. Leaders must secure agents and code at inception, enforce controls at runtime, and validate defenses independently.
Read at the sourcePrevention in agent-generated code is architecturally solved—but choosing controls that protect security without slowing development remains the challenge.
Read at the sourceAI applications can pass security scans yet remain exploitable through chained attacks across models, tools, data, and business workflows. Learn how DAST, AI pentesting, and red teaming work together to expose end-to-end risk.
Read at the sourceSee how Snyk’s Remediation Agent uses security intelligence, breakability analysis, and validation to turn vulnerabilities into mergeable pull requests.
Read at the sourceA benchmark of secure, functional vulnerability fixes across JavaScript, Java, and Python shows Snyk Intelligence helps frontier models break past a 72–75% performance plateau.
Read at the sourceThe Agent Baseline defines 35 controls across six security outcomes—but the right starting point depends on how your organization uses agents. Learn how to sequence controls for coding, internal, and production agents.
Read at the sourceA real Evo Continuous Offensive Security assessment uncovered 33 confirmed vulnerabilities in a multi-tenant enterprise SaaS, including tenant-wide compromise and critical authorization flaws.
Read at the sourceGet answers to 20 common questions about continuous offensive security, AI penetration testing, DAST, and AI red teaming.
Read at the sourceAI model risk depends on how a model is deployed. Learn how Evo combines adversarial testing, attack impact, and deployment context to help teams compare models and enforce policy.
Read at the sourceSnyk Secrets is now generally available, bringing contextual ML detection, secure-at-commit prevention, and unified secrets governance to the Snyk AI Security Platform.
Read at the sourceSnyk Evo Continuous Offensive Security brings autonomous, AI-powered pentesting to the 350 days between traditional tests, uncovering exploitable flaws attackers can find first.
Read at the sourcekeyv 6.0.0 and ten related npm releases shipped install-time malware. See affected versions, hashes, detection steps, and safe remediation order.
Read at the sourceExplore Snyk’s first Agentic AppSec capabilities: an autonomous Remediation Agent that fixes vulnerabilities and Malicious Code Defense that blocks risky packages before they ship.
Read at the sourceSnyk Studio integrates with Snowflake Cortex Code to scan AI-generated code, dependencies, and containers for vulnerabilities during development.
Read at the source