An exploit is any computing operation(s) that can cause unintended or unanticipated behavior of a system, all by taking advantage of a vulnerability. Put simply, an exploit is when a vulnerability is exploited.
Exploits can be a sequence of code, data packets, user input, hardware component, or technology architecture — anything that can maliciously take advantage of vulnerabilities in the technology.
Let’s take a look at exploits in this article.
A flaw in technology that can lead to security threats is called a vulnerability. An exploit is the next step in the playbook of the threat actor. It is the means and actions by which the vulnerability is leveraged to realize a malicious consequence.
This act — also known as a hack —is designed to infiltrate into a network, escalate user privileges, access sensitive data and/or modify the functionality of the target system against its intended or authorized use.
(Related reading: vulnerabilities, threats, and risk, explained.)
Technology changes all the time. New technology solutions replace legacy systems, with the goal of improved functionality and performance. These modern technologies are complex, designed for higher performance and scale. Vendors are encouraged to enhance functionality to serve evolving user demands.
A natural consequence to all this change is vulnerabilities and bugs. These emerge organically in technologies that are developed without extensive testing, and particularly in the technology industry where vendors must compete on scale and speed of innovation.
In some cases, a security vulnerability remains under the radar after it is discovered by malicious actors who continue to exploit it until vendors release a security patch. These vulnerabilities that are discovered and exploited by attackers before the app owner is aware of the issue or has a chance to fix it are known as zero-day exploits.
You’ve likely heard of a few of these notorious exploits, such as:
Others infamous examples include Heartbleed, Pegasus Spyware, and BlueKeep.
In other cases, a vulnerability is well-known and the security patch is released to the general-public. However, some end users continue to use vulnerable technologies without updating them. These are called Known Exploits. KEs are everywhere: one-third of connected devices (IoT) are vulnerable at any given moment. Perhaps more worrisome: 99% of cybersecurity exploits rely on previously known vulnerabilities.
Exploits are not limited to flaws in the technology. In fact, a majority of cyberattacks exploit the human element, taking the form of:
Social engineering typically exploits the lack of security awareness and an unsuspecting behavior of a user. In this case, threat actors may impersonate a legitimate and trustworthy entity when communicating with their targets.
Typically, the communications are designed to draw users into clicking a link, aiming to get the user to either:
The malicious payload is typically designed to infiltrate a network, escalate user privileges, and leak sensitive information to the threat actors.
Other exploits target the technology vulnerabilities directly. These bugs may exist within the network, hardware or software components, as well as user-input prompts and data processed within a service. Common examples of external attack vectors are:
An estimated one-third of cyberattacks remain undetected and under the radar until it’s too late. Often, these attacks are uncovered only after a costly data leak incident is executed.
(Indeed, research from IBM shows that the average time to detect a cyberattack is 277 days. That’s a lot of time for bad actors to do serious damage.)
This delay comes down to an important reason: inadequate monitoring and observability of the targeted systems, and the sophisticated nature of the attack.
Enterprise IT networks are complex.
The network nodes generate large volumes of log data in real-time. Employees frequently engage in shadow IT practices. Sensitive data is stored externally in public cloud data centers and transmitted over insecure Internet channels without encryption. The network resources also function in silos.
Comprehensive visibility into network operations at the process-level, across all nodes and all data centers across geographic locations is no easy task. This behavior gives rise to security risks:
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The other key challenge is the monitoring and identification of anomalous behavior in data access and transmission. Modern exploits are sophisticated and can leak data without raising flags.
For example, in the case of privilege escalation attacks, a compromised user account gains enhanced privileges to access and modify sensitive business data and resources. In this case, security solutions may not classify these actions as anomalous — considering the user attributes that allow for the necessary access privileges.
In the larger context however, the anomaly may be more evident. Contextual view is important: understand how one user account acts with respect to its historical behavior and other user accounts of similar hierarchical levels accessing the same data resources.
There are two key solutions to defend against sophisticated exploits: technology solutions and ongoing security awareness.
The first solution is to employ advanced data-driven technologies that are capable of identifying anomalies in a dynamic context. For example, an AI-powered security solution that can continuously train on new user behaviors and infer changing usage patterns.
Both abilities are critical because exploits are now available “as a service” on the Dark Web — anyone can use widely available exploits kits to bring down your IT systems.
The second, and perhaps more important, is to enhance security awareness and vigilance among your workforce against social engineering ploys and spear phishing.
Like everything in cybersecurity, technology can help reduce risk. But when humans are caught unawares or want to intentionally do harm? There’s no guaranteed defense for that.
See an error or have a suggestion? Please let us know by emailing ssg-blogs@splunk.com.
This posting does not necessarily represent Splunk's position, strategies or opinion.
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