Threat teams are staying on high alert because AI-powered threat campaigns are becoming more common. Updated playbooks, closely related to runbooks, are essential for these teams. Currently, they face the risk of falling behind.
The rapid rate of change in AI threats is making security teams reassess their playbooks, increase update schedules, and throw out those developed recently.
It is now absolutely necessary to update playbooks in real time to be ready for the new attacks that are going to be released.
AI is Everywhere
There’s no doubting the exponential growth of AI. From Generative AI to chatbots, indeed it is everywhere. Next up is Agentic AI and analysts say it will be bringing more threats with it. The threats range from autonomous attacks, data theft, and vibe hacks.
In recent reports, some AI models have shared security frameworks and findings that underscore the fact that things are moving quickly in AI and LLMs, and for some, perhaps too quickly.
Anthropic Claude 4
For example, Anthropic’s Claude 4 Opus was found to be able to code for 7 hours straight but also will try to blackmail engineers who attempt to shut it down. Researchers have now discovered that Anthropic’s Model Context Protocol (MCP) has a vulnerability that allows hackers to run arbitrary code remotely.
Google Deepmind
When it comes to AI, most researchers have been most concerned about protecting against a weakness known as Prompt Injection. There hasn’t been a solution to the problem until recently.
Google has developed a new approach that eliminates the need for AI models to self-evaluate. CaMeL, an acronym for Capabilities for Machine Learning, is the name of the new method. Simon Wilson, the researcher who coined the term prompt injection, is saying that it is the first real way to fix the vulnerability.
From Hero to Zero: Obsolete Security Playbooks
Playbooks are losing validity because they can’t keep pace with the fast-changing world of cyberthreats that are evolving, sophisticated, and now, AI-powered. Some of the reasons their playbooks have gone from hero to zero include:
- Expanded and Complex Attack Surfaces
Most AI systems need broad data access and have sprawling dependencies. These increase the risks exponentially for prompt injection, data poisoning, and supply chain attacks.
- Obsolete Signature Detection
Traditional tools such as antivirus and firewalls rely on outdated threat signatures to identify threats. It leaves them out of the loop in most cases where custom malware, zero-day attacks, and quickly evolving attacks are in play.
- Security Models Outdated
Many traditional playbook models assume a secure network perimeter and don’t address compromised credentials, insider threats, or the fluidity that exists in network environments that leverage cloud, remote work, AI toolsets, and mobile devices. - A Lack of AI-Specific Protections
Legacy tooling typically doesn’t monitor AI training phases or secure AI model weights. The result is that it leaves critical vulnerabilities unaddressed. AI-specific attack vectors now need new security strategies that go beyond traditional cybersecurity measures.
Why It’s Important Now
AI security playbooks are critically important right now because the AI threat landscape is changing rapidly and is more unpredictable than traditional cybersecurity protections can handle. To protect themselves from AI-driven threats, businesses need to make security decisions faster and with more risks than ever before. Some of the key reasons include:
Rapidly Advancing and Sophisticated AI Threats
The rise of AI-generated misinformation and deepfakes now threatens to undermine trust in audio, visual, and text content. New security measures, like integrating AI watermarking and content validation into security playbooks, are necessary to overcome these challenges.
Erosion of Trust in Digital Content
The rise of AI-generated misinformation and deepfakes now threatens to undermine trust in audio, visual, and text content. New security measures, like integrating AI watermarking and content validation into security playbooks, are necessary to overcome these challenges.
Faster and Riskier Security Decisions
AI innovation’s speed is forcing security teams to make quicker, ofttimes riskier decisions and discard year-old playbooks for more adaptive and agile strategies that can keep up with evolving threats and autonomous AI attacks.
The Need for AI-specific Incident Response
AI systems need to have tailored incident response playbooks and guidelines that address the unique vulnerabilities specific to AI, such as prompt injections, adversarial attacks, and model tampering.
Dynamic and Complex AI Environments
AI security requires the implementation of zero trust principles, which should include continuous monitoring, real-time threat detection, and strict access controls to prevent unauthorized data access, model exploitation, and adversarial manipulation. Traditional playbooks can’t cover these adequately.
Expanding Attack Surfaces and Identities
The attack surface grows and identities multiply due to AI systems integration across business infrastructures. This makes the inclusion of identity-first security and AI-powered threat detection as essential components of modern playbooks imperative.
Increasing Frequency of AI-Powered Attacks
Security firms say the recent surveys show that most businesses expect to face AI-driven attacks daily, which highlights the need for robust AI security playbooks to assist in proactive detection, mitigation, and response to these evolving threats.
The Best Strategy for AI Security Playbooks
Organizations that have not yet initiated an AI security playbook face significant challenges in effectively implementing a fast-paced playbook. Teams must focus on agility, integration, and continuous improvement to stay ahead of threats.
Some experts recommend the following guidance:
- Make sure processes, people, and technology are in line with established frameworks such as NIST, CSF, and NIST AI RMF, which will let you provide a strong baseline for AI security.
- Identify the AI models that are in use, what data they are ingesting, and the specific business objectives they are serving.
- Integrate security controls from model development, training, and deployment to runtime monitoring. In addition, use model management systems with versioning, access controls, and lineage tracking to maintain governance.
- Apply zero trust principles and network segmentation to minimize attack surfaces and contain breaches quickly.
- Continual auditing of AI systems and promptly applying patches and updates to software and dependencies to close any emerging vulnerabilities.
- Integrate AI-specific threat modeling and risk assessments.
Keeping playbooks updated in real time is critical to keeping AI security playbooks effective amid quickly evolving threats, and businesses should adopt these update strategies:
Integrate Adversarial Testing and Red Teaming
By incorporating adversarial machine learning exercises and AI-specific penetration tests into routine security assessments, your team can uncover vulnerabilities before attackers can exploit them.
Embed AI-specific Incident Response Protocols
Create and keep updated official guidelines for responding to incidents that are specific to AI systems, focusing on unique threats such as manipulating autonomous agents and indirect prompt injection. These protocols should be iteratively improved as new tactics and techniques are uncovered.
Use Established AI Security Frameworks
Updates should follow guidelines from frameworks like NIST, AI Risk Management Framework (AI RMF), and OWASP Top 10 for LLMs to make sure all new AI risks are addressed and that we meet changing rules.
Businesses don’t always need new tools for security. Organizations can strengthen their AI security by utilizing the tools they already have, planning the implementation of SOAR, and continuously making improvements. Artificial intelligence is here for businesses to use for threat hunting, security, and more. AI security playbooks quickly become outdated. To stay ahead of threats, organizations need to work at keeping playbooks updated.