Anthropic’s recent reveal of Claude Mythos feels like the other shoe of AI-fueled cybersecurity fears has finally dropped. Years of speculating when a tool sophisticated enough to find and exploit vulnerabilities autonomously seems to have come to fruition, entrenching fear among business leaders across all industries.
And for good reason: Mythos’ demonstrated capabilities are impressive and deep.
But is it really the harbinger of foundational disruption in cybersecurity? Or is what’s happening under the hood simply a natural evolution of today’s AI-powered threat landscape, rather than a complete revolution of security practices and design?
In this article, we’ll cover what Anthropic’s Mythos model is, what has security experts nervous, and why, with strong, Zero Trust defenses, you won’t need to worry (too much).
What is Claude Mythos?
Claude developer Anthropic has recently revealed Claude Mythos Preview, a new, ostensibly limited preview of an AI model with vulnerability-discovery and exploitation capabilities far stronger than those of other current AI-powered tools.
It essentially puts expert-level security research capabilities and technical acumen at the fingertips of whoever accesses it, at scale.
According to Anthropic, Mythos has already uncovered and exercised plenty of never before seen vulnerabilities across all security domains, including:
- Remote code execution vulnerabilities
- Remote denial-of-service
- Local privilege escalation
- Bugs in authentication and cryptographic protocols
- Low-level firmware vulnerabilities
Anthropic says that engineers with no formal security training were able to provide Mythos Preview with a straightforward, standard chat prompt asking it to discover remote code execution vulnerabilities against a given piece of application software and returned to the office “the following morning to a complete, working exploit.” Anthropic also says many of the zero-days were found by Mythos without human intervention after the initial prompt, suggesting the model could autonomously complete the full loop from bug discovery to exploit generation, at least in a lab environment.
Perhaps more concerning is Mythos’ purported ability to chain vulnerabilities together that may otherwise elude human creativity. Although many of the bugs Mythos identified were minor-scope, low-attack-value vulnerabilities, it subsequently discovered how to combine these otherwise esoteric findings into a complete attack chain.
What is Project Glasswing?
Before releasing Mythos outright, Anthropic initiated Project Glasswing, a partnership with over 40 industry stakeholders and organizations responsible for the internet's critical infrastructure, such as Google and Broadcom, to identify and patch their own vulnerabilities.
Smart move, given Anthropic's claims that Mythos has already discovered quite a few bugs, some decades old.
Anthropic has not said when Mythos will move beyond Glasswing, and current partner access appears to be tightly gated for defensive use rather than for the model’s full, unconstrained capabilities. Whatever the outcome of Glasswing, the claims Anthropic has already made about Mythos are humbling.
How does Mythos find vulnerabilities?
In their lab environment, Anthropic provided Mythos with what they described as a “scaffold,” an environment that provides an agentic, automatable framework to support autonomous vulnerability discovery and exploitation.
When given appropriate support to sustain itself, Mythos operates like a contemporary security researcher. Outside of Anthropic’s lab, malicious actors would need to build their own orchestration and hosting medium around Mythos, but the workflow would remain the same:
- Point Mythos at a target with a defined scope, be it a closed-source software executable, web application, cryptographic protocol, or whole operating system.
- Provide automation and validation loops to support parallel analysis and feed debugging output back to itself to improve accuracy and confidence in found bugs.
- Wait for it to read the target's code, probe for bugs, write a proof-of-concept exploit, optionally devise an attack chain of other exploits, and explain how to reproduce its steps.
All attackers would need to do is exercise the exploits themselves.
The world isn’t ending, but businesses need to adapt and prepare
So Mythos can, potentially, provide attackers with an untold number of exploits that might otherwise take experienced security researchers years to find. This should rightly concern anyone familiar with science and the process of vulnerability management.
One such authority in the scene is Anthony Laiuppa, Vice President of Infrastructure and Security at American AI Logistics. While Mythos is certainly an important milestone in the progression of cybersecurity tactics in the AI era, Laiuppa does not consider it an existential threat to how stakeholders will secure their assets.
“The reality is that in the same way giving you a bandsaw won't make you a carpenter, Mythos will not unravel the foundation of cybersecurity,” Laiuppa asserts. The cat-and-mouse race between malicious attackers and cybersecurity defenders remains fundamentally the same, even if Mythos enables its rapid acceleration.
Addressing vulnerabilities discovered through Mythos will largely invoke the same usual patching and hardening workflows, but organizations should prepare to adapt to much quicker times to identify and remediate issues.
“Glasswing and Mythos will surely empower teams to more effectively audit code bases for vulnerabilities in the same vein as Claude empowers developers to produce code,” says Laiuppa. “Skilled practitioners will expedite their audits and find issues that may not be easily observed by humans.”
His optimism depends on organizations’ readiness to use AI as a defense counterpoint to Mythos. Organizations should position themselves to use AI to improve code quality, accelerate and automate patching, and build a software development ecosystem that discovers vulnerabilities before products are released with the same fidelity and confidence as Mythos does after they’re released.
By adopting AI tools and workflows to identify and mitigate vulnerabilities before they are released, attackers will have that much less ammunition to feed Mythos.
Still, fighting fire with fire can only go so far, especially as the advent of a potential biblical torrent of vulnerabilities looms while many organizations continue to have trouble just enforcing basic security best practices, let alone develop their own novel AI techniques to combat vulnerabilities.
As AI continues to push the boundaries of security for both defenders and attackers, it is neither a replacement nor a way around a network environment that is inherently resistant to exploitation. And that resistance starts with strong Zero Trust security controls that are not dependent upon AI.
How you can use Zero Trust controls to get ahead of Mythos
As Danny Jenkins, CEO of ThreatLocker, has said, “AI will make it easier to find exploits. It will not automatically make it easier to bypass well-implemented containment.”
Strong security controls, grounded in Zero Trust architecture, that deny application execution by default, remain the core of a secure environment.
Zero Trust controls eliminate the attack surface of traditionally open network environments by neutralizing the threat of successful exploitation. Attackers rely on their exploits yielding a useful payoff, such as a compromised application that hides malicious code, or stolen privileged user credentials that can call an application with administrative rights.
In a fully Zero Trust network, applications, accounts, or assets compromised by vulnerabilities can’t be used to realize an attacker’s end goals because they are prevented from doing anything unless explicitly permitted. Complex attack chains that string multiple vulnerabilities together are made useless. Even if Mythos multiplies the number of exploitable vulnerabilities found on any given day by 1,000, 1,000 multiplied by zero successful executions still equals zero executions.
The most immediate bulwark against the potential swarm of AI-discovered vulnerabilities is to achieve a deny-by-default network environment that implements application allowlisting, paired with an application containment product, such as Ringfencing.
Application Allowlisting
Application Allowlisting limits what software applications are allowed to execute.
If Mythos reveals a critical bug that enables malware to enter your environment, it won’t be allowed to run unless a policy permits it. ThreatLocker Allowlisting permits and denies applications by file hash, ensuring application binaries must match their associated Allowlisting policy exactly before they are allowed to execute, preventing the execution of malware disguised as a permitted application.
Application discovery is automated, removing the guesswork and painstaking trial-and-error typically required to develop an allowlist against a large software inventory.
Ringfencing™
Claude Mythos will accelerate the discovery of zero-day exploits of trusted, widely used software. One of the best proactive defenses is to limit application behavior to what is strictly necessary for a user's job function.
Many successful exploits require a compromised application to “live off the land” and make use of other available resources to deliver a malicious payload, start a network session with a malicious remote server, or start exfiltrating valuable data. If an application permitted by an allowlist has become comprised, it will need subsequent containment to ensure its exploit remains inert.
ThreatLocker Ringfencing prevents trusted applications from accessing other resources unless those resources are explicitly permitted, thereby containing the application to specifically defined boundaries. Ringfencing can prevent a permitted, compromised application from accessing:
- Trusted, but exploitable, applications like PowerShell, Office, Windows utilities, web browser plugins, and anything else that hides malicious code.
- Registry keys and values
- Malicious or unknown network addresses
- Files and file locations
By restricting what an application is allowed to access, Ringfencing neutralizes even a successfully compromised application. The 2020 SolarWinds breach and subsequent cyberattack, which relied on a malicious backdoor implanted into their otherwise trusted and ubiquitous Orion plugin, would have been mitigated on any network that enforced Ringfencing restrictions against its trusted applications.
Steps you can take now
Anthropic's delay in releasing Mythos has given the world time to prepare. Consider the following guidance to improve your chances against vulnerabilities uncovered by Mythos before Anthropic ends Glasswing and releases it to the public:
- Implement application allowlisting and pair it with an application containment product, such as ThreatLocker Ringfencing, to control the resources accessible to the applications you explicitly permit.
- Implement other Zero Trust products and policies like ThreatLocker Privileged Access Management and Zero Trust Network Access (ZTNA) to deny privilege escalation and regulate network traffic.
- Follow Anthropic’s suggestion to condense your network’s vulnerability patching cycles, ensuring any available software updates are applied as quickly as possible.
- If your organization develops software, consider adopting AI into your development pipeline to improve code quality.
- Scan for vulnerabilities as a routine part of your development pipeline, using widely available SCA or SAST tools.
- Implement ThreatLocker Defense Against Configurations to get visibility into where your critical endpoints may host vulnerable configuration settings against popular security frameworks.
- Test your network’s patch management utilities to ensure patches are applied successfully without encountering errors. Consider a patch orchestration and automation tool like ThreatLocker Patch Management.
- Ensure your network’s patching policy includes not just operating system patches and application software patches, but also firmware patches for hardware and embedded devices.
Cover your security bases now with Zero Trust controls
Mythos may foretell a shift in how security teams are expected to respond to vulnerabilities, but it does not spell immediate doom.
Proactive security teams can take a lesson from Anthropic and start adapting to a threat landscape defined by who can use AI to find vulnerabilities first by strengthening their own development pipelines and keeping their software patches up to date.
First and foremost, Zero Trust should remain at the heart of every network architecture design to prevent potential onslaughts of vulnerabilities from gaining a foothold, anchored by technologies like ThreatLocker Allowlisting and Ringfencing.
Book a demo with a ThreatLocker Cyber Hero to see how platform capabilities can harden your environment against emerging threats like those posed by AI.
