An elite security researcher has flagged concerns that the bug bounty competition era may be coming to an end, as AI systems become sophisticated enough to outpace even the most experienced human researchers. Valentina Palmiotti, operating under the name Chompie, established herself as the most successful individual competitor at Pwn2Own Berlin, the globally renowned hacking competition, where she secured nearly $70,000 in competition winnings by identifying critical vulnerabilities in leading software platforms. Yet despite her triumph, she raised alarm that advanced AI models—particularly Claude Mythos, developed by Anthropic—will eventually prevent for security researchers to compete. “I competed in Pwn2Own this year because I believed it might be my last chance,” she informed BBC News, drawing attention to worries that AI-driven vulnerability discovery will substantially alter the bug bounty programmes across the industry.
The Pwn2Own champion’s pivotal achievement
Chompie’s leading position at Pwn2Own Berlin demonstrated the outstanding ability needed to triumph at the most challenging globally hacking challenge. On the first day of the event, she executed a complex assault against an Nvidia-linked system, securing $20,000 for her efforts. Rather than become complacent, she promptly went back to her lodgings to get ready for the next challenge, entering what she calls “zombie hacker mode”—an heightened condition of unbroken effort sustained by energy drinks and adrenaline that lasted through the night.
The toll of this relentless pursuit became clear when video of the event showed Chompie on stage looking simultaneously elated and exhausted after breaching a Linux-based system to obtain an additional $50,000 prize. She had laboured from 6pm to 6am without sleep, a punishing twelve-hour marathon that she acknowledged was far from ideal. Yet such dedication has become common practice amongst top-tier competitors, who drive themselves to extreme limits of human endurance to claim success at the renowned yearly competition. Chompie’s total earnings of nearly $70,000 reflected not just technical expertise but absolute commitment.
- Compromised Nvidia-linked system for $20,000 on day one
- Worked continuously for twelve hours without rest for second attempt
- Gained access to Linux system earning additional $50,000
- Described intense competition mode as “zombie hacker” state
How machine learning is transforming the cyber threat environment
The adoption of AI technology into cybersecurity has significantly transformed how security researchers approach their work. Tools like Claude Code have served as crucial tools, enabling researchers to speed up their vulnerability discovery processes and refine their testing methodologies. For competitors like Chompie, these intelligent platforms have provided a strategic advantage during gruelling marathon sessions, permitting them to function at higher efficiency whilst sustaining the intensity required to perform at top-tier events. The technology has made more accessible certain aspects of security testing, rendering complex approaches more accessible to a broader range of security professionals across the world.
However, this technological revolution has created a concerning contradiction. Whilst existing artificial intelligence systems serve as helpful supplements to human knowledge, increasingly sophisticated models risk make human workers redundant entirely. Anthropic’s Claude Mythos has previously shown the magnitude of this disruption, said to have uncovered 1,600 security flaws across hundreds of software programmes—a capacity that far exceeds what individual hackers can accomplish through traditional methods. The company has limited availability to government bodies and specialist security organisations, acknowledging the potential for both beneficial and harmful applications of such advanced systems.
The existing advantage for researchers working with humans
At the moment, ethical hackers occupy what Chompie describes as a “sweet spot” where artificial intelligence serves as an enabler rather than a replacement. Current AI tools are particularly effective at accelerating routine tasks, automating code analysis, and suggesting research directions that might otherwise necessitate hours of manual investigation. For security researchers conducting work in high-pressure environments—whether competing at Pwn2Own or conducting vulnerability assessments for organisations like IBM X-Force—these tools have become vital efficiency enhancers. The human element remains paramount, requiring creativity, intuition, and strategic thinking that current AI systems cannot adequately reproduce.
This joint advantage has permitted champions to push their operational boundaries further than previously possible. By transferring computational heavy lifting to machine learning systems, elite hackers can direct their mental energy on tackling intricate challenges and innovative exploitation techniques. The technology has enhanced human capability rather than displaced it, fostering a collaborative dynamic where the combined efforts of humans and machines are essential for achieving objectives. Yet this balance seems fleeting, with next-generation technologies already emerging.
The upcoming turning point
The cybersecurity community confronts an upcoming technical inflection point as next-generation AI models emerge. GPT 5.5 Cyber and comparable platforms promise capabilities that will substantially surpass human performance in vulnerability discovery. Unlike existing systems that enhance researcher capabilities, these sophisticated systems are designed to operate with limited human involvement, possibly uncovering and leveraging security flaws at speeds and scales that humans cannot match. This shift constitutes a watershed moment for the hacking landscape, where conventional expertise may become insufficient against AI-driven approaches.
Chompie’s decision to compete at Pwn2Own this year demonstrates a growing unease within the hacking community about the continued feasibility of human-led contests. As AI systems develop greater capability, the opportunity for human-dominated bug bounties and penetration testing challenges may swiftly diminish. The limitation on Claude Mythos to select institutions emphasises how seriously security experts perceive this challenge, yet such constraints offer only fleeting respite. The period of competitive vulnerability discovery that has shaped ethical hacking for decades appears poised for transformation within the near future.
Differing opinions on humanity’s future in cyber security
Whilst Chompie’s worries about AI dominance resonate throughout the information security field, not all IT security specialists share her gloomy assessment. Some argue that human insight, originality and judgment will always hold core importance in vulnerability research. They point to the unpredictable nature of security challenges and the value of contextual knowledge that machines have trouble reproducing. These optimists propose that rather than substituting human expertise, advanced AI will keep developing as a instrument that improves the entire profession, allowing researchers to address more sophisticated challenges whilst upholding human supervision and moral boundaries.
The debate demonstrates a wider tension within cybersecurity regarding technological progress and professional standing. Key figures in the sector recognise that AI will certainly reshape bug bounty programmes and hacking competitions, but they emphasise that human expertise stays essential in strategic decision-making and threat analysis. Major firms including Anthropic have deliberately controlled availability of advanced systems specifically because they recognise the risks of unchecked AI-driven vulnerability detection. This cautious strategy indicates the time ahead may include combined approaches where humans and AI collaborate under strict governance, rather than complete replacement of skilled hackers with self-governing systems.
- Human creativity vital for new offensive approaches AI cannot anticipate
- AI regulation and restricted access may maintain market advantages
- Hybrid human-AI teams likely to define the future of cybersecurity
Impact on defenders and attackers equally
The expansion of AI-powered vulnerability discovery introduces a double-edged challenge for the cybersecurity landscape. Whilst ethical hackers and vulnerability experts have traditionally served as the first line of defence, uncovering weaknesses before malicious actors can exploit them, the democratisation of AI tools risks create parity. If advanced systems become widely accessible, cybercriminals could theoretically discover vulnerabilities at volume, potentially outpacing the ability of defenders to patch systems. This asymmetry could fundamentally alter the economics of cybersecurity, forcing organisations to allocate substantially greater resources in defensive measures and swift remediation capabilities to compensate for expedited vulnerability discovery.
Conversely, the identical AI capabilities could improve defensive operations dramatically. Security teams furnished with advanced AI tools could theoretically detect and fix vulnerabilities faster than ever before, potentially keeping pace with threats. The critical variable lies in access and control. If AI vulnerability discovery tools stay closely guarded to approved security organisations and governments, as Anthropic currently ensures with Mythos, defenders may preserve their superiority. However, should such technologies eventually leak or be reverse-engineered, the consequences could be severe, making the issue of prudent rollout and access controls essential to cybersecurity’s long-term security.
The illicit hacking dimension
The prospect of AI-assisted flaw identification in the hands of cybercriminals represents perhaps the most alarming scenario facing the security community. Criminal threat actors have repeatedly shown their ability to weaponise new technologies faster than defenders can respond. If organised crime groups gain access to models like Mythos, they could conduct automated searches for exploitable flaws across vast swathes of software and infrastructure, essentially automating the process of identifying vulnerabilities. This would grant them unparalleled velocity and breadth in locating targets, possibly exceeding the capacity of ethical hackers and defensive personnel to respond effectively.
Anthropic’s decision to restrict Mythos access demonstrates acute awareness of this danger. The company explicitly acknowledged the model’s potential for misuse, restricting access to chosen authorities and cybersecurity institutions. This gatekeeping approach, whilst controversial, represents a pragmatic recognition that unfettered AI access could empower criminal enterprises disproportionately. However, such limitations may prove temporary. History suggests that advanced systems eventually proliferate beyond their intended boundaries, prompting difficult inquiries about the duration for which responsible deployment practices can contain instruments created expressly to uncover concealed vulnerabilities in computer systems.
Responsible implementation as the critical factor
The future trajectory of ethical hacking and cybersecurity is heavily influenced by how the technology industry handles AI vulnerability discovery tools. Establishing comprehensive governance frameworks, access controls and accountability mechanisms will be critical for stopping misuse whilst enabling legitimate security research. Industry cooperation between technology companies, security researchers, governments and law enforcement could help establish standards for ethical use. Such frameworks might include restricted licensing agreements, usage monitoring, and international cooperation to prevent tools from reaching criminal networks. Without proactive governance, the market edge currently enjoyed by ethical hackers could disappear within years.
Chompie’s choice to take part at Pwn2Own whilst the chance persists reflects a broader urgency within the cybersecurity research community to establish norms and protections before AI substantially transforms the landscape. Security professionals, policymakers and technology companies must work together to ensure that advanced artificial intelligence systems reinforce rather than weaken cybersecurity protections. This requires transparency about capabilities, honest assessment of risks, and readiness to enforce limitations that may inconvenience researchers but safeguard critical infrastructure. The timeframe to create responsible standards may be narrowing, making immediate action vital to maintaining human expertise and ethical oversight in an increasingly automated security ecosystem.