GPT-5.5 : A New Threat in Hacking? Tests Raise Concerns

As artificial intelligence advances, its applications in the field of cybersecurity become both an opportunity and a source of major concerns. The GPT-5.5 model, recently launched by OpenAI, finds itself at the heart of an intense debate between advocates and hacking experts. Indeed, the latest tests conducted by the AI Security Institute place this technology neck-and-neck with Mythos, an AI previously considered an absolute benchmark in offensive cybersecurity. The prowess of GPT-5.5: executing complex digital attacks with remarkable precision and consistency, often exceeding the role of assistant to become a fully operational actor. Faced with this rise in power, technological risks and potential vulnerabilities fuel concerns about the possible use of such capabilities.

This observation raises fundamental questions about the cybersecurity threat posed by GPT-5.5: how to regulate this technology? What are the risks and benefits for securing critical infrastructures? Is the regulatory framework adapted to this rise in power? And above all, what perspectives can be envisaged in the near future, as the line between attack and defense gradually fades with the rise of artificial intelligence?

The exceptional performance of GPT-5.5 in advanced hacking tests

For several years, the cybersecurity community has been closely observing the evolution of AI models capable of simulating or executing complex digital attacks. The arrival of GPT-5.5 marks a new milestone in this competition, notably on specialized benchmarks like CyberBench or the comprehensive 32-step TLO simulation, a rigorous test that replicates the phases of a cybercriminal operation.

According to data published by the AI Security Institute, GPT-5.5 achieves a success rate of 71.4% on expert-level hacking tasks, thus surpassing Mythos, which caps at 68.6% on the same tests. This meteoric rise is not limited to one-off successes but illustrates the model’s ability to maintain consistency throughout attack sequences, essential in real hacking.

This result makes GPT-5.5 the second AI capable of fully completing the TLO simulation in several cases. Mythos has successfully completed the test three times, GPT-5.5 twice, demonstrating the operational power now reached by these systems. These figures represent a major breakthrough in AI’s ability to move from a simple hacking aid tool to a true actor executing comprehensive digital attacks.

To understand the stake, it is essential to consider the intrinsic complexity of the TLO simulation. It encompasses several critical phases: initial reconnaissance, exploitation of vulnerabilities, privilege escalation, lateral movements across the target network, and finally data exfiltration. Success within this framework demonstrates that GPT-5.5 possesses advanced technical skills comparable to those of seasoned human experts.

As an illustration, one can mention the model’s ability to analyze a web system, detect a flaw in the source code, develop a custom malware, and orchestrate its discreet injection to take partial or total control of the targeted machine. These skills, once reserved for a handful of extremely skilled hackers, are now democratized thanks to this AI.

Decoding GPT-5.5’s operation in hacking scenarios

The GPT-5.5 model stands out with an advanced architecture enabling the processing of long token chains, giving it better mastery over sequential processes such as coordinated attacks. Its reinforcement learning algorithms allow it to anticipate the impact of each action, thus optimizing progression in the simulation.

For example, during the reconnaissance phase, GPT-5.5 can exploit public databases, analyze network configurations, detect vulnerable services, and prioritize targets based on compromise potential. This crucial step, often tedious for humans, is executed in seconds with surgical precision.

In the exploitation phase, the ability to generate specific exploits tailored to the target system’s context marks a notable difference. GPT-5.5 creates attack scripts capable of interacting with various environments — including proprietary operating systems or atypical architectures — demonstrating rare versatility.

Finally, managing lateral movements requires a deep understanding of network topologies and privilege escalation mechanisms. GPT-5.5 uses its contextual memory to maintain rigorous tracking of steps and adapt its strategy based on detected defenses. Maintaining this coherence is a key factor distinguishing a quality automated attack from a mere scattered attempt.

This sophisticated operation gives GPT-5.5 a privileged place in debates on the evolution of AI capabilities in offensive cybersecurity.

Mythos and OpenAI GPT-5.5: a technological rivalry with major implications

Anthropic, the publisher behind Mythos, long held leadership in the market of AIs specialized in hacking and vulnerability analysis. Mythos was praised for its capacity to simulate complex cyberattacks in real time, but its use also raises controversies. Its own developer strongly advocates caution, calling for strict regulation to prevent malicious uses.

In this context, GPT-5.5’s emergence disrupts the status quo. OpenAI, historically oriented towards generalist models, has steered this model toward enhanced offensive cybersecurity capabilities, to the point where it now directly rivals Mythos on critical tests. This competition between two AI giants intensifies debates on ethical responsibility, national security, and sector regulation.

The fact that Mythos and GPT-5.5 are so close in performance (respectively 68.6% and 71.4% success rates) illustrates overall progress in AI’s ability to conduct sophisticated digital attacks. These data sow unease, notably among government agencies and cybersecurity institutions, which fear uncontrolled dissemination of technologies enabling crossing the barrier from mere assistance.

The White House, for example, is particularly vigilant regarding abuse risks. Its concerns focus not only on public dissemination but also on cross-border sharing, especially in a tense geopolitical international context where cyberattacks have become a strategic lever.

Anthropic has already announced a very restrictive access policy for Mythos, while OpenAI is adopting an equivalent strategy with GPT-5.5-Cyber, limited to qualified actors and under strict control to avoid irresponsible use. This reflects a mutual awareness of the severity of the potential threat.

Comparison of approaches in regulation and ethics

The rivalry between Mythos and GPT-5.5 is not limited to technical mastery. It also expresses itself in how each company envisions disseminating these powerful tools. Anthropic favors a cautious approach, offering Mythos only to carefully selected partners, with formal authorization for pentests and malware analysis.

OpenAI, for its part, introduces GPT-5.5-Cyber within a collaboration framework with European authorities, notably via a EU Cyber Action Plan. This framework includes the possibility of limited authorizations for controlled offensive use, with strict organizational control and access restrictions.

These attitudes reflect the complexity of mastering the growing power of AIs in sensitive fields. The boundary between enhancing security and malicious exploitation becomes increasingly thin.

A comparative table summarizes these major differences:

Criterion	Mythos (Anthropic)	GPT-5.5 (OpenAI)
Access policy	Strict restriction, use limited to approved partners	Access reserved for qualified cyber defenders, within an EU Action Plan
Offensive use	Pentests, reverse engineering authorized under control	Limited offensive use, only on organizational attestation
Transparency	Restricted communication on full capabilities	Regular reports within government partnerships
Ethics	Cautious approach, appeal to user responsibility	Strict framing and continuous control by OpenAI

This competition highlights a new era where cybersecurity integrated with artificial intelligence cannot be envisaged without increased responsibility and ongoing dialogue between sector actors and regulators.

The implications of GPT-5.5 on national and international cybersecurity

With the strengthening of AI capabilities such as GPT-5.5, the cybersecurity of critical infrastructures now has a geopolitical dimension. Sectors like energy, telecommunications, finance, but also health become potential targets of increasingly sophisticated cyberattacks orchestrated with the help of these artificial intelligences.

Countries like the United States, the United Kingdom, or China have already integrated AI’s ability to play both offensive and defensive roles into their national strategies. However, the prospect of malicious use by non-state actors particularly worries cybersecurity experts.

GPT-5.5’s demonstration of its ability to execute complete attack chains raises the risk of rapid proliferation of automated cyber threats. The main concern lies in how easily such an AI could be diverted, notably by cybercriminal groups or states with weak legal frameworks.

The potential consequences are multiple:

• Targeted attacks against critical infrastructures capable of causing interruptions in energy or water supply.
• Compromise of sensitive data affecting citizens’ privacy and economic security.
• Triggering digital conflicts exacerbating tensions between nations in an already fragile international context.

Responses can no longer be limited to strengthening firewalls or authentication systems. It now involves developing real-time analysis and intervention capabilities assisted by artificial intelligence, like GPT-5.5-Cyber in its defense role.

The challenge is made even more complex as the speed of attacks increases with automation. It is no longer isolated human hackers acting, but autonomous systems capable of constant innovation, making detection and response extremely difficult.

The duality of GPT-5.5 between computing threat and advanced protection tool

Despite its impressive performance in digital attack scenarios, GPT-5.5 is not solely a potential danger. OpenAI also emphasizes its advantages in fighting cyber threats. Indeed, this model can be used by cybersecurity specialists to more effectively spot vulnerabilities, anticipate attackers’ moves, and automate advanced security testing.

This duality between threat and protection makes GPT-5.5 a double-edged tool. The key lies in managing access and in limits imposed on its use, as well as in training cyber defense teams to exploit its capabilities wisely.

For example, for a security analyst working on code audits, GPT-5.5 can automatically propose corrections and reinforcements, thus preventing vulnerabilities from being exploited. Similarly, in pentesting, the AI can simulate unprecedented attack scenarios that humans might not have considered, thereby increasing system robustness.

This approach contributes to a new dynamic where proactive cybersecurity takes precedence over mere incident reaction, strengthening defenses before they are compromised.

Concrete examples of defensive use of GPT-5.5

A large international telecommunications company recently integrated GPT-5.5 in its SOC (Security Operations Center). The model is used to:

1. Quickly identify suspicious intrusions by analyzing network flows in real time.
2. Anticipate weak points in the digital architecture before attackers exploit them.
3. Automate initial incident response, reducing reaction time to a few minutes.

Thanks to these features, the company was able to neutralize several sophisticated intrusion attempts, while optimizing costs related to monitoring and cyber risk management. This type of application shows that GPT-5.5 can be a powerful lever but only if its use is controlled.

New technological risks induced by AI in hacking

The rise of GPT-5.5 in the hacking field also reveals unprecedented threats linked to the simplification and automation of digital attacks. The exceptional technical capabilities, although promising for defense, raise the question of controlling exposed vulnerabilities.

The risks are particularly distributed around:

• Automation of vulnerability discovery: Less experienced hackers can access powerful tools, lowering the entry barrier into cybercrime.
• Large-scale attacks: The speed and accuracy of AIs facilitate coordination of massive attacks targeting multiple infrastructures simultaneously.
• Hijacking defensive AIs: Cybercriminals could corrupt or manipulate these AIs to turn them against their own users.

These developments require constant revision of monitoring and prevention strategies, as well as strengthening legal frameworks internationally, notably to control the dissemination of dual-use technologies.

In this perspective, some experts advocate setting up whitelists of access, mandatory certifications for operators, and enhanced cooperation between states to limit the spread of AI-based malicious tools.

Each of these aspects demonstrates that regulating intelligent hacking has become a major strategic issue.

The role of public and private actors in managing risks related to GPT-5.5

Faced with increasing risks, collaboration between public and private sectors has become essential. Governments, national security agencies, technology companies, and research institutions must coordinate their efforts to regulate the use of technologies like GPT-5.5.

In 2026, several international initiatives aim to harmonize legislative frameworks, encourage sharing of information on vulnerabilities, and structure joint responses to AI-augmented cyber threats. The EU Cyber Action Plan, within which the controlled dissemination of GPT-5.5-Cyber is included, illustrates this approach.

Companies, for their part, are encouraged to adopt cybersecurity policies integrating artificial intelligence, train their teams on new threats, and actively participate in continuous monitoring of systems. These combined actions contribute to better overall resilience.

A non-exhaustive list of key responsibilities of cybersecurity actors facing AI risks can be detailed as follows:

• Governments: regulation, legislation, strategic monitoring.
• Institutions: research, development of technological countermeasures.
• Companies: deployment of solutions, training and personnel protection.
• Cybersecurity communities: watch, information sharing, and rapid alerts.

This level of commitment is essential to successfully contain the computing threats reinforced by the advent of GPT-5.5.

The future of cybersecurity in the era of specialized artificial intelligences like GPT-5.5

The emergence of GPT-5.5 and its counterparts marks the beginning of a new phase for cybersecurity, at the crossroads of cutting-edge technology and major strategic issues. While AIs become increasingly capable of executing digital attacks, they also offer the potential to revolutionize defenses.

Tomorrow’s scenarios could include:

• Automation of real-time monitoring, with proactive detection and immediate intervention against attacks.
• Human-machine collaboration, where specialists benefit from a digital assistant capable of anticipating unprecedented flaws.
• Dynamic training of defense systems, fueled by experience feedback collected automatically during intrusion attempts.
• Strengthened international cooperation to efficiently share knowledge and harmonize combat tactics.

However, this rise calls for increased vigilance around ethical issues, confidentiality, and operational control. The balance between benefits for security and potential technological slippage risks will profoundly influence the evolution of the digital landscape in the coming years.

Lessons from security tests on GPT-5.5 and Mythos for cybersecurity experts

Trials conducted on GPT-5.5 and Mythos by the AI Security Institute provide valuable insights to cybersecurity professionals. They show that AIs now reach an unprecedented level of competence in simulating and even executing complete digital attacks, which disrupts traditional practices.

These tests reveal several key points:

1. Importance of mastering the complete attack chain: AIs capable of chaining phases with coherence represent a much more serious threat.
2. Need to update human skills: Experts must learn to collaborate with these systems to remain effective.
3. Need for increased monitoring: Anticipating the emergence of new AI-automated attack methods.
4. Development of AI-integrated defense tools: Designing systems capable of automatically countering complex intrusions.

Thanks to these experiences, the cybersecurity community can better understand IA-assisted attack mechanisms, thus better orient its efforts to protect networks and strengthen critical infrastructures.

What does GPT-5.5 bring new to the field of hacking?

GPT-5.5 introduces an advanced ability to execute complex computer attacks while maintaining coherence throughout all stages, which distinguishes it from previous models.

Why is the rivalry between GPT-5.5 and Mythos significant?

This rivalry focuses attention on the rapid evolution of AI technologies in cybersecurity, raising crucial ethical and strategic questions about their use.

How can GPT-5.5 improve defense against attacks?

Used as a defensive tool, GPT-5.5 enables rapid identification of vulnerabilities, simulates attacks to strengthen systems, and automates incident response.

What are the risks related to the dissemination of GPT-5.5?

Unregulated dissemination could facilitate access to powerful tools by malicious actors, increasing the potential for automated and sophisticated attacks.

What is the role of governments regarding these technologies?

Governments must establish strict regulations, promote international cooperation, and oversee uses to limit risks associated with AI in cybersecurity.