By Emma Zaballos, Senior Researcher, CyCognito April 22, 2025 5 Min Read
The recent DeepSeek security breach has once again highlighted the significant vulnerabilities in artificial intelligence (AI) systems and raises alarming questions about where the exposed data may have ended up.
Shortly after DeepSeek’s release, security researchers uncovered extensive vulnerabilities in the system’s infrastructure. Publicly exposed sensitive user data and proprietary information like this often makes its way to the Dark Web — a thriving underground market where stolen data is routinely traded, sold, and exploited.
This latest incident serves as a stark warning for organizations rushing to adopt AI technologies without implementing proper security controls. As AI systems become increasingly integrated into core business operations, the security implications extend far beyond traditional cybersecurity concerns, potentially leading to catastrophic damage to operations and reputation.
Security Nightmare Unravels as Researchers Probe DeepSeek
The vulnerabilities discovered in DeepSeek reveal a disturbing pattern in how organizations approach AI security. Wiz Research uncovered a publicly accessible ClickHouse database belonging to DeepSeek, containing more than a million lines of log streams with highly sensitive information. This exposed data included chat history, API keys and secrets, back-end details, and operational metadata.
The security nightmare didn’t end there. The exposed database allowed full control over database operations, potentially enabling attackers to access internal data and perform privilege escalation within DeepSeek’s environment. Security researchers identified more than a million lines of log streams containing sensitive information, highlighting the extensive nature of the breach.
The leak exposed data from more than a million users, including chat histories and potentially personally identifiable information (PII). Such large-scale exposures often attract immediate attention from cybercriminals on the Dark Web. Adding to the severity, unencrypted user data was being sent over the Internet due to the DeepSeek iOS app globally disabling App Transport Security (ATS). The app also used an unsecure and deprecated encryption algorithm (3DES) with hard-coded encryption keys, potentially allowing decryption of sensitive data fields.
Beyond the exposed database, SecurityScorecard’s Strike team identified outdated cryptographic algorithms and weak data protection mechanisms. Researchers found SQL injection vulnerabilities that could give attackers unauthorized access to user records. The exposed database contained sensitive information, including chat histories, API keys, and back-end details — precisely the type of data highly valued by cybercriminals on Dark Web marketplaces.
Perhaps most concerning, the DeepSeek-R1 model showed alarming failure rates in security tests: 91% for jailbreaking and 86% for prompt injection attacks.
Adding to these concerns, phishing sites targeting DeepSeek users have already emerged, aiming to steal user data and crypto wallets, suggesting that malicious actors are actively exploiting the company’s user base and security weaknesses.
Stolen DeepSeek Assets Become Prime Dark Web Merchandise
The exposed DeepSeek assets represent prime targets for Dark Web trading, where stolen data becomes valuable merchandise. The Dark Web is a thriving underground market where illegal goods, including stolen data and corporate vulnerabilities, are openly traded. This hidden economy poses a direct and growing threat to businesses worldwide, as recent high-profile breaches have demonstrated.
The type of data exposed in the DeepSeek breach is particularly valuable on Dark Web markets:
- Leaked credentials: Login details for corporate and personal accounts are sold in bulk. These credentials can enable attackers to take over accounts, breach networks, and escalate further attacks.
- Privileged access: Administrative accounts and API keys provide entry to critical infrastructure, cloud services, and sensitive networks. This allows attackers to move laterally and escalate privileges within systems.
- Sensitive corporate information: Chat histories containing potentially confidential discussions, intellectual property related to AI models, and operational details create significant competitive risks as attackers could potentially steal or reverse engineer core AI technology.
- Personally identifiable information: Names, communication patterns, and other personal details often stemming from chat histories can be used for identity theft, fraud, and social engineering schemes.
The DeepSeek breach demonstrates how quickly AI security vulnerabilities can translate into marketable assets on the Dark Web, creating long-term risks for both the company and its users.
Organizations Must Seize Control of AI Security
While AI security may seem daunting, organizations aren’t powerless. The key lies in developing comprehensive exposure management strategies before rolling out AI technologies. From our experience working with enterprises across industries, here are the essential components of an effective program:
- Focus on external exposures. With more than 80% of breaches involving external actors, organizations must prioritize their external attack surface. This means continuously monitoring internet-facing assets, especially AI endpoints and related infrastructure.
- Find everything. Discovery must be comprehensive across all business units, subsidiaries, and acquisitions. This includes cloud services, on-premise systems, and third-party integrations. AI systems often have complex dependencies that create unexpected exposure points.
- Test everything. Implement continuous security testing on all exposed assets, not just those deemed critical. This includes regular application security assessments, penetration testing, and AI-specific security evaluations. Traditional “crown jewels” approaches miss critical vulnerabilities in seemingly low-priority systems.
- Prioritize based on risk. Evaluate threats based on their potential business impact rather than technical severity alone. Consider factors like data sensitivity, operational dependencies, and potential regulatory implications when prioritizing remediation efforts.
- Share broadly. Integrate exposure management into existing security processes through automation and clear communication channels. Ensure findings are shared with relevant stakeholders and feed into broader security operations and incident response processes.
Proactive Defense Becomes Essential in Dark Web Era
The Dark Web’s hidden dangers aren’t going away, but businesses can outpace them with the right strategy. Accepting the reality of exposure is the first step. From there, consistent monitoring, proactive action, and a focus on closing vulnerabilities will help protect your organization from the growing threat landscape.
The DeepSeek incident serves as a critical wake-up call. Security considerations must be built into AI initiatives from the ground up, with continuous monitoring and testing becoming standard practice. The stakes are simply too high to treat AI security as an afterthought, especially when the Dark Web stands ready to capitalize on every vulnerability.
Story from Darkreading.com
Emma Zaballos
Senior Researcher, CyCognito
Emma Zaballos is senior researcher at CyCognito. She previously worked as an analyst monitoring threat actor behavior on the Dark Web before focusing on threats to the US healthcare sector. She has given talks at DerbyCon and ShmooCo.
