If you’ve ever found yourself sifting through a maze of emails and Jira tickets searching for one crucial piece of context, you’re not alone. Security analysts worldwide face this frustration regularly, needing critical insights dispersed across platforms to assess alerts and manage incidents effectively. This data is often hidden within internal wikis, ticketing systems, and email threads—trapped in unstructured formats that defy quick, programmatic searching.
The difficulty in accessing contextual data slows response times and burdens security teams when performing investigations. Yet, advances in AI now enable security teams to access vital information swiftly and precisely. By leveraging the power of agentic security solutions to analyze, process, and recall vast amounts of unstructured data, analysts can quickly answer questions during investigations instead of combing through scattered sources for context.
The Challenges of Managing Institutional Knowledge in Security Operations
In security operations, quick access to organizational knowledge is essential. Analysts often need specific context to assess alerts accurately and understand the scope and severity of a threat. However, this vital information is frequently scattered across multiple platforms and stored in unstructured formats, making it difficult to locate when needed most.
The fallible nature of human memory adds to the complexity; security analysts may struggle to remember where to find specific information or details, leading to time-consuming searches through various sources.
Unstructured Knowledge and Its Impact on Security Investigations
Security investigations require quick, reliable access to context, yet much of this information is stored in unstructured formats, making it challenging to locate and utilize. For instance, crucial details may be buried in Jira tickets, permissions in SharePoint, or job titles within a company directory, requiring analysts to search through multiple platforms manually. Compounding this difficulty is the dispersion of storage locations. Platforms like Google Workspace, Slack, Office 365, Jira, ServiceNow, Gmail, Exchange, Microsoft Active Directory, and Microsoft Entra ID each contain puzzle pieces.
Delays and Operational Costs of Fragmented Context
The operational costs of fragmented context in security investigations can be significant. When analysts struggle to locate information independently, they often turn to colleagues for assistance and then wait for responses. This not only interrupts others’ work but also creates inefficiencies that can ripple throughout the team.
When there’s a true security incident, these delays can severely hinder the speed of response, increasing the organization’s risk. Even when responding to a false alert, the time analysts spend searching for the right information represents a valuable resource that could be better allocated to proactive security measures.
Agentic Security Can Unlock Contextual Knowledge in Security Operations
While these challenges have long been a burden on security teams, advances in AI now offer promising solutions for managing knowledge in security operations, especially when dealing with unstructured data. AI SOC analysts are uniquely adept at processing vast volumes of information from various sources—like emails, tickets, and wikis—rapidly retrieving the specific context needed during investigations. Unlike human analysts, who get tired and forget things, AI SOC analysts maintain concentration and have perfect memory recall. Once stored in memory, an agentic solution will always be able to remember which hosts have special functions or which user accounts are in the accounting department.
Agentic security solutions can autonomously pull relevant data from sources like audit logs, file access records, and email exchanges. For example, in the case of an Office 365 insider alert, an AI SOC analyst can swiftly examine audit logs and communication histories to determine who shared a file, the level of access provided, and whether any external sharing was authorized. Additionally, AI SOC analysts can analyze activity patterns, such as IP addresses, to confirm that user behavior aligns with established norms and to flag any anomalies.
How AI Can Streamline Human-Driven Investigations
Agentic security systems can also streamline human-driven investigations by providing on-demand access to organizational knowledge. While agentic AI systems typically operate autonomously, they can also be deployed as interactive chatbots, enabling security analysts to retrieve critical information through simple, conversational queries. This setup allows analysts to ask questions and receive quick, relevant answers without extensive searching, streamlining the investigation process.
For example, an AI agent can support AWS investigations by quickly answering questions about user access, activity logs, or recent changes within the environment. In one AWS investigation, an AI agent assisted a security admin by accessing institutional knowledge stored in Jira. Responding to the admin’s questions, the AI chatbot identified the account admin, clarified its purpose for production deployments in the region, and confirmed access restrictions for the Automation team—all based on details from Jira tickets. This rapid retrieval of context allowed the admin to progress without time-consuming searches, showing how AI chatbots efficiently distill critical organizational knowledge for security inquiries.
Preserving Privacy During Insider Threat Investigations
No security professional likes reading through their colleague’s email, but unfortunately, that’s sometimes required when investigating potential insider threats. AI agents offer a more privacy-conscious approach by filtering and presenting only the communications directly pertinent to the investigation. By narrowing the scope to essential data, AI agents reduce the need for analysts to read through messages that fall outside the investigation’s focus, helping maintain employee privacy. This capability ensures that investigations remain thorough without compromising privacy, allowing analysts to access the information they need with minimal intrusion into unrelated communications.
How Dropzone AI Facilitates Efficient Knowledge Management
Dropzone AI’s mission is to equip cyber defenders with unlimited intelligence. Our AI SOC analyst autonomously handles routine alert investigations and streamlines the collection of contextual information. Pre-trained on core security investigative techniques, Dropzone AI bridges the gap between routine task management and meaningful threat assessment.
Dropzone AI’s integrations allow it to connect seamlessly with popular security tools, from SIEMs and EDRs to identity providers and email systems. Once integrated, Dropzone AI begins autonomously gathering and organizing data across these platforms, removing the need for time-consuming manual searches. Its user-friendly deployment—typically completed in under an hour—means security teams can begin seeing results almost immediately. To learn more request a demo today.
