The Mythos Moment: Enterprises Must Fight Agents with Agents

Agentic AI is making it more difficult for teams to build a strong security posture. They now have to reconcile with combating agentic AI attack chains that keep probing for vulnerabilities and, after identifying such vulnerabilities, craft dynamic, sequential attacks that can automatically pivot based on the defenses they encounter. And this is not the worst of it. Such attacks occur at machine speed, making them difficult to stop.Throwing more tools at this threat landscape is not the answer. It will just lead to more fragmentation, giving AI-driven cyberthreats a field day to exploit and create vulnerabilities. What is needed is a different security foundation.New Security Architecture for the AI EraA new security framework for the AI era should stand on three critical pillars: visibility, context, and autonomous control.Network Visibility: An attack launched in a distributed environment can easily spread across users, applications, and the cloud services of the IT infrastructure. Detecting such an attack based on a single element is impossible. A unified network is needed, one that provides complete visibility into the attack lifecycle by capturing and inspecting traffic across all domains over time.Platform Context:Visibility without context, however, creates noise rather than intelligence. The focus should be on understanding what is happening, and a converged platform helps you do that by correlating security and networking data in a single pane of glass, rather than piecing together signals from discrete tools post-incident. This architectural model ensures that context is not only provided but also preserved in real time for reconstruction later if needed. An AI attack begins with low-signal activities that appear benign in isolation but, with identified context, can be recognized as part of a larger attack sequence. This is actionable intelligence.Agentic Control:With attackers becoming autonomous and able to scale attacks at will and at speed, defense mechanisms must also operate at machine speed. Agentic systems can continuously analyze activity, identify emerging patterns, and dynamically generate protection. Slow, laborious human-led responses yield to security that responds in real time. Do not mistake this for automation; this is what I call autonomy in defense.Agentic systems can keep correlating activity across extended patterns, identifying patterns that appear benign, but as they continue viewing them over time, they appreciate their significance. In a threat theatre where attackers try to hide under the table with low-signal actions that culminate in serious incidents, continuous behavioral analytics are critical for staying on top of such threats.Agentic-Driven Defenses for a New Threat LandscapeTraditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

Throwing more tools at this threat landscape is not the answer. It will just lead to more fragmentation, giving AI-driven cyberthreats a field day to exploit and create vulnerabilities. What is needed is a different security foundation.New Security Architecture for the AI EraA new security framework for the AI era should stand on three critical pillars: visibility, context, and autonomous control.Network Visibility: An attack launched in a distributed environment can easily spread across users, applications, and the cloud services of the IT infrastructure. Detecting such an attack based on a single element is impossible. A unified network is needed, one that provides complete visibility into the attack lifecycle by capturing and inspecting traffic across all domains over time.Platform Context:Visibility without context, however, creates noise rather than intelligence. The focus should be on understanding what is happening, and a converged platform helps you do that by correlating security and networking data in a single pane of glass, rather than piecing together signals from discrete tools post-incident. This architectural model ensures that context is not only provided but also preserved in real time for reconstruction later if needed. An AI attack begins with low-signal activities that appear benign in isolation but, with identified context, can be recognized as part of a larger attack sequence. This is actionable intelligence.Agentic Control:With attackers becoming autonomous and able to scale attacks at will and at speed, defense mechanisms must also operate at machine speed. Agentic systems can continuously analyze activity, identify emerging patterns, and dynamically generate protection. Slow, laborious human-led responses yield to security that responds in real time. Do not mistake this for automation; this is what I call autonomy in defense.Agentic systems can keep correlating activity across extended patterns, identifying patterns that appear benign, but as they continue viewing them over time, they appreciate their significance. In a threat theatre where attackers try to hide under the table with low-signal actions that culminate in serious incidents, continuous behavioral analytics are critical for staying on top of such threats.Agentic-Driven Defenses for a New Threat LandscapeTraditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

New Security Architecture for the AI EraA new security framework for the AI era should stand on three critical pillars: visibility, context, and autonomous control.Network Visibility: An attack launched in a distributed environment can easily spread across users, applications, and the cloud services of the IT infrastructure. Detecting such an attack based on a single element is impossible. A unified network is needed, one that provides complete visibility into the attack lifecycle by capturing and inspecting traffic across all domains over time.Platform Context:Visibility without context, however, creates noise rather than intelligence. The focus should be on understanding what is happening, and a converged platform helps you do that by correlating security and networking data in a single pane of glass, rather than piecing together signals from discrete tools post-incident. This architectural model ensures that context is not only provided but also preserved in real time for reconstruction later if needed. An AI attack begins with low-signal activities that appear benign in isolation but, with identified context, can be recognized as part of a larger attack sequence. This is actionable intelligence.Agentic Control:With attackers becoming autonomous and able to scale attacks at will and at speed, defense mechanisms must also operate at machine speed. Agentic systems can continuously analyze activity, identify emerging patterns, and dynamically generate protection. Slow, laborious human-led responses yield to security that responds in real time. Do not mistake this for automation; this is what I call autonomy in defense.Agentic systems can keep correlating activity across extended patterns, identifying patterns that appear benign, but as they continue viewing them over time, they appreciate their significance. In a threat theatre where attackers try to hide under the table with low-signal actions that culminate in serious incidents, continuous behavioral analytics are critical for staying on top of such threats.Agentic-Driven Defenses for a New Threat LandscapeTraditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

A new security framework for the AI era should stand on three critical pillars: visibility, context, and autonomous control.Network Visibility: An attack launched in a distributed environment can easily spread across users, applications, and the cloud services of the IT infrastructure. Detecting such an attack based on a single element is impossible. A unified network is needed, one that provides complete visibility into the attack lifecycle by capturing and inspecting traffic across all domains over time.Platform Context:Visibility without context, however, creates noise rather than intelligence. The focus should be on understanding what is happening, and a converged platform helps you do that by correlating security and networking data in a single pane of glass, rather than piecing together signals from discrete tools post-incident. This architectural model ensures that context is not only provided but also preserved in real time for reconstruction later if needed. An AI attack begins with low-signal activities that appear benign in isolation but, with identified context, can be recognized as part of a larger attack sequence. This is actionable intelligence.Agentic Control:With attackers becoming autonomous and able to scale attacks at will and at speed, defense mechanisms must also operate at machine speed. Agentic systems can continuously analyze activity, identify emerging patterns, and dynamically generate protection. Slow, laborious human-led responses yield to security that responds in real time. Do not mistake this for automation; this is what I call autonomy in defense.Agentic systems can keep correlating activity across extended patterns, identifying patterns that appear benign, but as they continue viewing them over time, they appreciate their significance. In a threat theatre where attackers try to hide under the table with low-signal actions that culminate in serious incidents, continuous behavioral analytics are critical for staying on top of such threats.Agentic-Driven Defenses for a New Threat LandscapeTraditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

Network Visibility: An attack launched in a distributed environment can easily spread across users, applications, and the cloud services of the IT infrastructure. Detecting such an attack based on a single element is impossible. A unified network is needed, one that provides complete visibility into the attack lifecycle by capturing and inspecting traffic across all domains over time.Platform Context:Visibility without context, however, creates noise rather than intelligence. The focus should be on understanding what is happening, and a converged platform helps you do that by correlating security and networking data in a single pane of glass, rather than piecing together signals from discrete tools post-incident. This architectural model ensures that context is not only provided but also preserved in real time for reconstruction later if needed. An AI attack begins with low-signal activities that appear benign in isolation but, with identified context, can be recognized as part of a larger attack sequence. This is actionable intelligence.Agentic Control:With attackers becoming autonomous and able to scale attacks at will and at speed, defense mechanisms must also operate at machine speed. Agentic systems can continuously analyze activity, identify emerging patterns, and dynamically generate protection. Slow, laborious human-led responses yield to security that responds in real time. Do not mistake this for automation; this is what I call autonomy in defense.Agentic systems can keep correlating activity across extended patterns, identifying patterns that appear benign, but as they continue viewing them over time, they appreciate their significance. In a threat theatre where attackers try to hide under the table with low-signal actions that culminate in serious incidents, continuous behavioral analytics are critical for staying on top of such threats.Agentic-Driven Defenses for a New Threat LandscapeTraditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

Platform Context:Visibility without context, however, creates noise rather than intelligence. The focus should be on understanding what is happening, and a converged platform helps you do that by correlating security and networking data in a single pane of glass, rather than piecing together signals from discrete tools post-incident. This architectural model ensures that context is not only provided but also preserved in real time for reconstruction later if needed. An AI attack begins with low-signal activities that appear benign in isolation but, with identified context, can be recognized as part of a larger attack sequence. This is actionable intelligence.Agentic Control:With attackers becoming autonomous and able to scale attacks at will and at speed, defense mechanisms must also operate at machine speed. Agentic systems can continuously analyze activity, identify emerging patterns, and dynamically generate protection. Slow, laborious human-led responses yield to security that responds in real time. Do not mistake this for automation; this is what I call autonomy in defense.Agentic systems can keep correlating activity across extended patterns, identifying patterns that appear benign, but as they continue viewing them over time, they appreciate their significance. In a threat theatre where attackers try to hide under the table with low-signal actions that culminate in serious incidents, continuous behavioral analytics are critical for staying on top of such threats.Agentic-Driven Defenses for a New Threat LandscapeTraditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

Agentic Control:With attackers becoming autonomous and able to scale attacks at will and at speed, defense mechanisms must also operate at machine speed. Agentic systems can continuously analyze activity, identify emerging patterns, and dynamically generate protection. Slow, laborious human-led responses yield to security that responds in real time. Do not mistake this for automation; this is what I call autonomy in defense.Agentic systems can keep correlating activity across extended patterns, identifying patterns that appear benign, but as they continue viewing them over time, they appreciate their significance. In a threat theatre where attackers try to hide under the table with low-signal actions that culminate in serious incidents, continuous behavioral analytics are critical for staying on top of such threats.Agentic-Driven Defenses for a New Threat LandscapeTraditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

Agentic systems can keep correlating activity across extended patterns, identifying patterns that appear benign, but as they continue viewing them over time, they appreciate their significance. In a threat theatre where attackers try to hide under the table with low-signal actions that culminate in serious incidents, continuous behavioral analytics are critical for staying on top of such threats.Agentic-Driven Defenses for a New Threat LandscapeTraditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

Agentic-Driven Defenses for a New Threat LandscapeTraditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

Traditional enterprise defenses cannot protect against a threat landscape led by autonomous attacks. Manual investigation or human-led escalation will only be playing catch-up. A future-ready enterprise defense should be an agentic, AI-driven system that enables day-to-day security operations at machine speed. This framework is best served by a same-day vulnerability protection agent that automatically generates and enforces protections the moment new threats are disclosed, closing the gap between CVE publication and remediation. It can also include a zero-day attack protection agent that continuously analyzes activity for early signs of unknown attacks, then dynamically creates and deploys protections before the attack chain can escalate. Together, these agents make the enterprise defense more continuous, coordinated, and immediate in its detection, interpretation, and response.When full lifecycle visibility, real-time contextual intelligence, and autonomous control come together, they enable a fundamentally new kind of mitigation. They enable an agentic defender to match agentic attackers in speed, scale, and continuous adaptation, while directing those capabilities toward protection rather than exploitation.Learn More at the AI Risk Summit | Ritz-Carlton, Half Moon BayRelated:Claude Mythos Finds 271 Firefox VulnerabilitiesRelated:Critical Vulnerability in Claude Code Emerges Days After Source Leak

Source: SecurityWeek