To effectively detect credential theft, organizations must collect and analyze logs from a variety of sources, including web servers, authentication systems, proxies, DNS servers, endpoint protection platforms, and network monitoring tools. Common signs of credential theft include multiple failed login attempts followed by a successful login, logins from unusual geographic locations or at odd hours, sudden changes in access patterns, and the use of compromised credentials to access sensitive data or systems. However, by correlating web logs with network indicators, security teams can piece together the subtle clues left behind and identify credential theft before it leads to major damage. Endpoint indicators, such as processes accessing browser credential stores or running known credential dumping tools, and network indicators, such as unusual outbound connections or data transfers, also play a crucial role in detection. Security information and event management (SIEM) systems can ingest logs from multiple sources, apply correlation rules, and generate alerts when suspicious patterns are detected. Endpoint logs should record process execution, file access, and command-line activity, while network logs provide insights into connections, data transfers, and communication with external servers. For example, a rule might flag a sequence where a user receives a suspicious email, visits a phishing site, and then logs in from an unusual location. By establishing a profile of normal user activity such as typical login times, locations, devices, and accessed resources organizations can more easily spot deviations that may indicate credential theft. Correlating web logs and network indicators is a powerful approach to detecting credential theft. However, when these events are correlated with other indicators such as visiting a phishing site or executing a suspicious process they can reveal a pattern consistent with credential theft. Web server logs should capture details about user authentication attempts, session creation, and access to sensitive resources. Credential theft occurs when an attacker acquires valid authentication information such as usernames, passwords, or session tokens through methods like phishing, malware, social engineering, or exploiting vulnerabilities in web applications. The process of log correlation involves collecting these logs, normalizing them into a consistent format, and applying analytical rules to identify suspicious patterns. Credential theft is a persistent and growing threat in the cybersecurity landscape, responsible for a significant portion of data breaches and security incidents. Over the next hour, file server logs record the account accessing sensitive financial documents and attempting to download large volumes of data. As credential theft techniques continue to evolve, organizations must regularly review and update their correlation strategies to stay ahead of attackers and protect their most valuable assets. Attackers who successfully steal credentials can gain unauthorized access to sensitive systems and data, often bypassing conventional security measures. Normalization is critical for effective correlation, as it allows security analysts and automated tools to connect related events across disparate data sources.
This Cyber News was published on cybersecuritynews.com. Publication date: Sun, 20 Apr 2025 18:15:13 +0000