According to the 1980’s cartoon G.I. Joe, “knowing is half the battle.” Unfortunately, threat actors often have more information than their targets, which is why they’re so successful. For developers and AppSec teams, having information about threat actor tactics, techniques, and procedures (TTPs) helps even the digital battlefield.
Threat intelligence feeds provide data about malicious actors and their activities that help you take proactive steps to secure your code.
What is threat intelligence?
Threat intelligence is data about threat actors’ motives, targets, and attack behaviors. By analyzing this data, security professionals can make informed decisions about risk mitigation strategies.
Threat intelligence can be broken up into four different categories:
- Strategic: trends and emerging risks focused on business impact rather than an attack’s technical aspect
- Tactical: TTP details that help identify Indicators of Compromise (IoCs) in systems
- Technical: forensic details, like URLs, used to trace threat actor activity
- Operational: clear, deep, and dark web chatter about an attack’s nature, intent, timing, and sophistication
The Importance of Threat Intelligence
Threat intelligence is the cybersecurity equivalent of the CNN news ticker at the bottom of the screen. It gives you the most up-to-date information about ongoing activities.
Threat intelligence is fundamental information about the attack landscape, like the context, mechanisms, indicators, or implications. It offers advice about remediating affected devices, applications, systems, or networks.
However, threat intelligence fails to provide actionable information about how an attack works across a specific application data flow. For example, attackers may be exploiting a vulnerability that one of your code libraries uses. Still, they may not be able to exploit it within the context of your business logic.
Challenges with using threat intelligence
While threat intelligence is valuable, many teams struggle to use it meaningfully.
Too many locations
Each category of threat intelligence can be found in a different place, so collecting and aggregating it becomes time-consuming.
Some examples of threat intelligence sources include:
- Social media posts
- Vendor blogs
- Security researcher blogs
- Government websites like the Cybersecurity and Infrastructure Security Agency (CISA)
- National Vulnerability Database (NVD)
Further, for developers and AppSec teams, this becomes even more challenging. While they can find information about TTPs or IoCs, the data focuses on exploits in an enterprise IT context rather than how to detect them embedded into the application’s code.
Too much information
With so much information available, identifying the most pertinent data becomes challenging. If you collect it manually, you now spend time reading, cross-referencing, and analyzing it. For example, using blogs to gain insight into TTPs is critical. However, you must read through them and pull out the relevant IoCs to look for trends and patterns.
Even if an AppSec team manages to correlate the data, they need to apply it to the code using a manual review adding even more time to the already lengthy manual code review process.
Automating with threat intelligence feeds
Organizations typically use threat intelligence feeds to automate many of these processes.
Enhanced accuracy for stronger security
With threat intelligence feeds, you eliminate the human error risks associated with manual review across various data sets. Threat feeds collect, correlate, and analyze the information for you, then provide a machine-readable version that integrates with your security tools. With automation, you no longer have to worry that someone overlooked a security risk impacting the code.
Real-time visibility for faster time-to-market
Since automated threat feeds scan continuously, you get the real-time visibility you need to use the data effectively. By incorporating threat feeds into your automated code scans, you can fix security issues as you build your application. Integrating security into your regular code reviews streamlines processes so you can meet deadlines.
Prioritize remediation by understanding impact
Developers and AppSec teams need threat intelligence that gives them context about attacker activities in the context of their code, not just enterprise IT environments overall. They need threat feeds that combine reachability with exploitability so they can prioritize their remediation actions. If attackers can’t exploit a vulnerability within the context of the application’s code, then its risk profile changes.
Qwiet AI Blacklight: The first AppSec threat feed
Qwiet AI’s Blacklight adds real-world threat information to scan results so that you can combine reachability with exploitability. Our preZero platform is the first automated code review technology to fully integrate a security threat feed into real-time code analysis. With Blacklight, you can prioritize fixes by focusing on the exploits, threat actors, ransomware, and botnets actively exploiting vulnerabilities in the wild.
Try Qwiet AI’s preZero platform for free to see how it streamlines processes and improves security.