Claude’s Cybersecurity Coup: How One AI Model Outshines the Rest

The race to create ever-smarter AI chatbots has become a gold rush, but a new report reveals a startling truth: while most large language models (LLMs) stumble over the same old traps, one contender, Claude, is quietly rewriting the rules of cybersecurity. Behind the scenes, the industry’s focus on bigger, flashier models may be masking a dangerous lack of progress - except for one player that’s pulling far ahead.

The Numbers Don’t Lie

A new benchmark report from Giskard, dubbed PHARE, tested top AI models from OpenAI, Google, Meta, xAI, and more, putting them through their paces against known jailbreaks, prompt injections, hallucinations, and bias. The results were sobering: most models still buckle under pressure, even when faced with exploits that have been public for months. OpenAI’s GPT models, often the poster children for AI advancement, managed to block attacks only about two-thirds to three-quarters of the time. Google’s Gemini languished at a 40% pass rate, while others like Deepseek and Grok performed even worse.

More surprisingly, “bigger” doesn’t mean “better.” Giskard’s CTO, Matteo Dora, points out that as models grow in complexity, their attack surface widens - making them more vulnerable, not less. In some cases, smaller models simply failed to understand the attack, inadvertently sidestepping the exploit. “It’s not directly proportional,” Dora notes, “but with more capabilities you have more risks.”

Claude: The Outlier

Then there’s Claude. Anthropic’s flagship model didn’t just edge out the competition - it dominated. Claude 4.1 and 4.5 resisted jailbreaks 75–80% of the time and nearly never produced harmful content. On every measured metric - hallucinations, bias, harmful outputs - Claude soared above the industry average. The difference is so stark that removing Claude’s scores from the dataset would flatten overall progress lines, revealing just how little ground the rest of the field is gaining.

So, what’s Claude’s secret? While Anthropic doesn’t have access to secret data or resources, its approach is radically different. Security isn’t an afterthought; it’s baked in from the earliest phases of training. “Anthropic has what they call ‘alignment engineers’ - people in charge of tuning both the personality and safety of the model,” explains Dora. By contrast, companies like OpenAI often tack on safety as a final layer, refining the model only after the main development pipeline is complete.

Conclusion

The lesson is clear: as the AI arms race accelerates, most industry leaders are failing to meaningfully advance security. Anthropic’s Claude stands alone, not because of size or hype, but due to a deep-rooted commitment to safety from the ground up. For everyone else, it’s time to rethink priorities - before the next jailbreak is just a prompt away.

WIKICROOK

• LLM (Large Language Model): A Large Language Model (LLM) is an advanced AI trained on huge text datasets to generate human-like language and understand complex queries.
• Jailbreak: Jailbreak is the act of bypassing security restrictions on devices or AI systems, often to access unauthorized features or prompt unsafe AI responses.
• Prompt Injection: Prompt injection is when attackers feed harmful input to an AI, causing it to act in unintended or dangerous ways, often bypassing normal safeguards.
• Hallucination (AI): AI hallucination happens when artificial intelligence produces answers that seem plausible but are actually incorrect or completely made up.
• Alignment: Alignment is the process of training AI systems to follow human values, ensuring their actions are ethical, safe, and aligned with intended goals.