In cybersecurity, several related but divergent meanings have been ascribed to the phrase “red flags.” The phrase has roots in fraud and insurance, popularized by the FTC as part of the 2003 Red Flags Rule under the Fair and Accurate Credit Transactions Act requiring credit issuers to build programs that detect identity theft via warning signs of fraud.
In some context, cyber red flags are the glaring warning signs that something is already going wrong or missing, such as an alert from an intrusion detection system, a data exfiltration indicator, or a risk and compliance control gap. Because these signals often fall under the Detect function of the NIST Cybersecurity Framework, they often manifest when an adverse event has already happened, especially when adversaries are using tactics like lateral movement or malware deployment aligned with MITRE ATT&CK techniques.
While this imagining of cyber red flags has its place in a healthy information security program, it is highly limited in its focus upon indicators that register only after initial compromise. While the most recent Verizon Data Breach Investigations Report highlights timelines in breach detection, it is important to clarify that detection often occurs in weeks rather than months. Depending on the industry, some breaches may still go undetected for over one hundred days. Relying solely on reactive indicators locks organizations into a detect-and-respond posture, slamming the door shut after the intruder is already inside.
“Red flags” is a common phrase in cyber broking and M&A contexts as well, where it is used slightly differently. In these circles, “red flags” tend to be gaps in an organization’s perimeter security posture. They are often the most basic and critical cybersecurity controls representing the blocking and tackling of breach prevention. Within this context, application vulnerabilities visible from an unauthenticated, external scan or failure to enforce Multi-Factor Authentication (MFA) on perimeter systems are common red flags: detectable from the public Internet, discrete and tactical in nature, and notorious for their contributions to past security incidents.
Once again, categorization of these controls has its benefits. In the short-to-medium-term, they are most likely to contribute to a cybersecurity incident and should be triaged for remediation. An even smaller subset of insurance-focused red flags comprises the notion of pre-deal cyber diligence red flags, which might be material to the health of a transaction. In an M&A context, often only the most egregious security gaps rise to this level, with anything more subtle slated for remediation after a deal is closed. An understanding of an organization’s cybersecurity posture as aligned with these types of red flag controls is valuable, but still incomplete. They can skew toward the descriptive and the superficial, without offering more predictive insights from deeper analysis.
To close that gap, organizations need to shift attention to predictive signals, which can be both tactical and strategic. Tactical indicators might be called “precursor indicators” or “anomalies,” and can include unusual reconnaissance scanning, atypical authentication attempts, or unusual phishing link clicks. These early warnings often appear long before ransomware begins encrypting files. By recognizing precursor activity, sometimes called Indicators of Attack (IoAs), security teams can intervene in the earliest stages of an attack. These signals often surface through user and entity behavior analytics tools, SIEM systems, or threat intelligence feeds. Catching them early can dramatically reduce dwell time and associated costs. Studies by the Ponemon Institute find that organizations that detect threats sooner can save as much as fifty percent compared to those that react later.
Underlying strategic signals are often more subtle and require discussion-based assessment or intensive audit sampling to uncover. Are Data Loss Prevention efforts reliant upon the manual tagging efforts of a single, overworked infrastructure engineer? Is access to a myriad of cloud applications managed in a spreadsheet, with inconsistent password standards and authentication requirements across each platform? These potential weaknesses lurk below the surface of a typical cyber red flags analysis but can undoubtedly contribute to incidents or other poor cybersecurity outcomes.
Consider the long-term dental health of a patient without a regular brushing schedule. A superficial review of his teeth might not reveal any visible cavities, but a deeper analysis might uncover poor health of the gums. Further discussion with the patient could in turn reveal an ad-hoc and unrefined commitment to oral maintenance. These precursor indicators would suggest a likelihood of future oral health concerns not evident from a superficial dental review.
This proactive posture fits inside modern resilience strategies, such as those articulated in NIST SP 800-160. The NIST standard frames security as a continuum of prevention, detection, and recovery. Incorporating attention to precursor activity strengthens prevention and enables rapid recovery if compromise occurs.
This is not to discount red flags completely. Rather, they should be seen as part of a spectrum: late-stage signals or control gaps that complement early warning signs and deeper information security program health checks. By layering detection across that spectrum, organizations gain true pre-emption.
Beyond improved detective capabilities, businesses are incentivized to invest in self-analysis beyond the lens of red flags by cyber insurance carriers, who are increasingly expecting evidence of preventative controls and often raise premiums or deny coverage for ignored or unaddressed warnings. Monitoring anomalies not only improves security posture but also aligns with insurance requirements and reduces financial and reputational risk, and this monitoring is enriched and improved when driven through cybersecurity reviews of threat, vulnerability, and residual risk.
Wrapping up, the adoption of the phrase “Red Flags” in cybersecurity borrows the post-event detection framework often from its precursor in Fraud Prevention, but its adoption in the context of cyber posture against the top underwriting concerns must not preclude analysis of more foundational flaws. Today the field needs language and models that emphasize anticipation and early disruption rather than waiting for crisis or aligning a cybersecurity program to antiquated terms to mis-prioritize control elements of a program.
The content provided herein is for general informational purposes only and should not be construed as legal, regulatory, compliance, or cybersecurity advice. Organizations should consult their own legal, compliance, or cybersecurity professionals regarding specific obligations and risk management strategies. While LevelBlue’s Managed Threat Detection and Response solutions are designed to support threat detection and response at the endpoint level, they are not a substitute for comprehensive network monitoring, vulnerability management, or a full cybersecurity program.
