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Before security engineers can even consider a response, they must assess the severity of each alert, which can range from a false positive to an active threat. This involves sifting through cloud logs for raw data, but these logs lack context, making it extremely challenging to connect the dots and pinpoint the root cause of each alert.
Daily alerts force teams to choose between thorough investigations, which hinder other duties, or focusing on tasks while potentially missing critical threats. The lack of context in alerts from Security Information and Event Management (SIEM) systems exacerbates the issue, preventing the identification of high-risk attack vectors.
Adversaries, who constantly evolve their tactics, techniques, and procedures (TTPs), gain an upper hand as they can act more swiftly than defenders can respond. This imbalance favors attackers, who can exploit the delays in detection and response.
Even with leading cloud security tools, companies often have incomplete visibility over their cloud environment. Triaging cloud alerts in the SIEM remains a manual, time-consuming process, further complicating security efforts.
Posture management solutions often provide only a momentary snapshot, lacking the continuous monitoring necessary to maintain an up-to-date view of the attack landscape. This means teams can often only look backwards, unable to anticipate the adversary’s next move based on current compromised assets.
Organizations struggle to maintain detection parity across different Cloud Service Providers (CSPs). Building effective cloud detection requires specialized knowledge, and teams spend excessive time writing custom rules that achieve only partial coverage. The complexity of cloud telemetry, scattered across various sources, makes manual correlation slow and error-prone.
Cloud Native Application Protection Platforms (CNAPPs) frequently leave gaps, treating each configuration change as an isolated event without correlating it to the broader attack. This siloed approach means security teams must investigate the entire scope of configuration changes during an attack, attempting to distinguish malicious changes from legitimate ones.
Stream Security pioneers Cloud Detection and Response by modeling all cloud activities and configurations in real-time to uncover adversary intent. It is the only real-time model fully aware of posture, behavior, and business impacts, enabling security teams to outpace adversaries and detect, investigate, and respond to cloud threats at the speed of the cloud.
Stream Security leads in Cloud Detection and Response, modeling all cloud activities and configurations in real-time to uncover adversary intent. The platform correlates activities by principles, helping security teams connect the dots and understand correlations among cloud operations. It reveals each alert's exploitability and blast radius to predict the adversary's next move, enabling security teams to detect, investigate, and respond with confidence, outpacing the adversary.