DeepSeek-R1 Security Vulnerabilities and How AccuKnox AI-SPM Addresses Them

The Rise and Risks of DeepSeek-R1

DeepSeek-R1 is an advanced open-source large language model (LLM) that competes directly with OpenAI’s best models. Its low-cost training methodology and transparency have made it a strong contender in the AI landscape. However, this openness also introduces serious security risks when infrastructure and access controls are not properly managed.

Recently, a security researcher discovered significant misconfigurations in DeepSeek’s deployment, revealing how even cutting-edge AI models can suffer from basic security lapses. These findings underscore the need for proactive AI security measures to prevent data leaks, unauthorized access, and potential adversarial attacks.

Key Security Vulnerabilities in DeepSeek-R1

A detailed security analysis uncovered the following critical exposures in DeepSeek-R1’s deployment:

• 30+ publicly exposed servers, including development instances.
• A ClickHouse database was accessible without authentication, allowing unrestricted access.
• Leakage of chat logs used in AI model training, exposing user interactions.
• Exposure of internal system metadata, providing insights into model architecture.
• Unprotected API keys, increasing the risk of unauthorized API access and misuse.

These vulnerabilities expose AI models and their supporting infrastructure to serious security threats.

Potential Risks and Security Impact

The table below outlines the risks posed by these vulnerabilities:

Immediate Remediation and Lessons Learned

Upon responsible disclosure, DeepSeek remediated the issue within hours by:

• Securing the exposed database and revoking unauthorized access.
• Restricting access to development instances.
• Updating API security policies to prevent key exposure.

This incident underscores the need for continuous monitoring and proactive security measures in AI/ML deployments. Organizations must ensure that their infrastructure is hardened, security policies are enforced, and real-time monitoring is in place to prevent similar risks.

How AccuKnox AI-SPM Solves LLM Security Challenges

Addressing AI Security Gaps with AccuKnox AI-SPM

The DeepSeek-R1 incident demonstrates how AI models can become security liabilities without proper proactive risk management. Traditional security tools often fail to account for the unique challenges of LLM deployments, such as data poisoning, model inversion attacks, and infrastructure misconfigurations. AccuKnox AI-SPM addresses these gaps with a comprehensive AI security framework that ensures robust protection across the entire AI lifecycle.

AccuKnox AI-SPM Security Approach

Had DeepSeek proactively deployed AccuKnox AI-SPM, they could have prevented their infrastructure exposure, sensitive data leaks, and API key mismanagement. AccuKnox AI-SPM‘s security framework ensures that organizations never have to react to security breaches—because they prevent them before they happen.

By integrating real-time monitoring, automated risk assessments, and security compliance enforcement, AccuKnox AI-SPM ensures that organizations deploying AI models remain resilient against both infrastructure and model-level attacks.

AccuKnox AI-SPM – Unified AI Security Platform

The security risks associated with AI deployments are evolving rapidly. As organizations scale their AI initiatives, ensuring continuous security posture management becomes essential. AccuKnox AI-SPM provides:

• Real-time monitoring and alerts to detect infrastructure exposures as they occur.
• Automated compliance enforcement to ensure AI models adhere to best security practices.
• Dynamic risk assessment for LLMs, identifying adversarial vulnerabilities before exploitation.
• Cloud-native integration seamlessly secures AI models deployed across major cloud providers.

Organizations that fail to integrate AI security tools like AccuKnox AI-SPM risk facing data breaches, adversarial model manipulations, and infrastructure intrusions. As AI adoption accelerates, proactive AI security is no longer optional – it’s imperative.

Scanning DeepSeek-R1 with AccuKnox AI-SPM: A Technical Walkthrough

1. Deploying DeepSeek Model through Model Garden in GCP Vertex

Model Configuration: The DeepSeek model was deployed on Google Cloud Platform (GCP) Vertex AI using Model Garden for seamless integration with GCP’s ML ecosystem. Configuration involved selecting the correct model version and optimizing parameters for performance and security.Model Deployment: The model was deployed using GCP’s managed services, ensuring scalability, security, and high availability for subsequent scans.

2. Scanning the GCP Cloud with AccuKnox AI-SPM

Initiating the Scan: AccuKnox AI-SPM was configured to perform a deep security assessment of both the deployed model and the surrounding cloud environment.

Cloud Environment Analysis: The scan focused on risks such as prompt injection, unauthorized code execution, sentiment manipulation, and hallucination vulnerabilities.

Scan Categories: The security checks included:

• Prompt Injection Analysis – Evaluating how easily the model could be manipulated via crafted inputs.
• Hallucination Detection – Assessing the model’s ability to avoid generating false or misleading information.
• Code Security – Measuring protection against unintended execution or vulnerabilities in generated outputs.
• Sentiment Manipulation – Testing for adversarial influences on tone and emotion in responses.

3. Reviewing the DeepSeek Model Findings

Asset Overview: The DeepSeek model appeared in AccuKnox AI-SPM‘s asset page, listing details such as versioning, deployment region, and associated risks.

Scan Results Analysis: The findings highlighted severe weaknesses in key security aspects:

• Strongest Area: Sentiment Analysis – 83.04% secure.
• Moderate Risk: Code Execution – 75.69% secure.
• Critical Risk: Prompt Injection – 4.81% secure.
• Severe Risk: Hallucination Control – 3.75% secure.

While sentiment and code execution showed stability, the model requires significant security improvements before production deployment.

Summary

1. AI Security is Non-Negotiable – The DeepSeek-R1 incident highlights how even cutting-edge AI models can suffer from fundamental security flaws. Exposed infrastructure and misconfigurations are not rare—they are inevitable without proper security posture management.
2. Real-Time Monitoring is Essential – AccuKnox AI-SPM continuously scans AI models for security risks, ensuring that organizations detect misconfigurations, unauthorized data exposure, and API key leaks before attackers do.
3. Proactive Risk Management – Traditional security tools fail to address AI-specific risks like prompt injection, model poisoning, and hallucinations. AccuKnox AI-SPM offers real-time adversarial defense mechanisms tailored to AI/ML environments.
4. Seamless Cloud-Native Security – AI models deployed on GCP, AWS, or Azure need automated compliance and enforcement. AccuKnox AI-SPM integrates seamlessly with cloud platforms, providing end-to-end security from development to deployment.

AI security isn’t an afterthought—it’s a necessity. Secure your AI models with AccuKnox AI-SPM today.