Skip to main content

Zero-day

 

Zero-day is a flaw in software, hardware or firmware that is unknown to the party or parties responsible for patching or otherwise fixing the flaw. The term zero day may refer to the vulnerability itself, or an attack that has zero days between the time the vulnerability is discovered and the first attack. Once a zero-day vulnerability has been made public, it is known as an n-day or one-day vulnerability.

Ordinarily, when someone detects that a software program contains a potential security issue, that person or company will notify the software company (and sometimes the world at large) so that action can be taken. Given time, the software company can fix the code and distribute a patch or software update. Even if potential attackers hear about the vulnerability, it may take them some time to exploit it; meanwhile, the fix will hopefully become available first. Sometimes, however, a hacker may be the first to discover the vulnerability. Since the vulnerability isn't known in advance, there is no way to guard against the exploit before it happens. Companies exposed to such exploits can, however, institute procedures for early detection.

Security researchers cooperate with vendors and usually agree to withhold all details of zero-day vulnerabilities for a reasonable period before publishing those details. Google Project Zero, for example, follows industry guidelines that give vendors up to 90 days to patch a vulnerability before the finder of the vulnerability publicly discloses the flaw. For vulnerabilities deemed "critical," Project Zero allows only seven days for the vendor to patch before publishing the vulnerability; if the vulnerability is being actively exploited, Project Zero may reduce the response time to less than seven days.

Zero-day exploits detection

Zero-day exploits tend to be very difficult to detect. Antimalware software and some intrusion detection systems (IDSes) and intrusion prevention systems (IPSes) are often ineffective because no attack signature yet exists. This is why the best way to detect a zero-day attack is user behavior analytics. Most of the entities authorized to access networks exhibit certain usage and behavior patterns that are considered to be normal. Activities falling outside of the normal scope of operations could be an indicator of a zero-day attack.

For example, a web application server normally responds to requests in specific ways. If outbound packets are detected exiting the port assigned to that web application, and those packets do not match anything that would ordinarily be generated by the application, it is a good indication that an attack is going on.

Zero-day exploit period

Some zero-day attacks have been attributed to advanced persistent threat (APT) actors, hacking or cybercrime groups affiliated with or a part of national governments. Attackers, especially APTs or organized cybercrime groups, are believed to reserve their zero-day exploits for high-value targets.

N-day vulnerabilities continue to live on and are subject to exploits long after the vulnerabilities have been patched or otherwise fixed by vendors. For example, the credit bureau Equifax was breached in 2017 by attackers using an exploit against the Apache Struts web framework. The attackers exploited a vulnerability in Apache Struts that was reported, and patched, earlier in the year; Equifax failed to patch the vulnerability and was breached by attackers exploiting the unpatched vulnerability.

Likewise, researchers continue to find zero-day vulnerabilities in the Server Message Block protocol, implemented in the Windows OS for many years. Once the zero-day vulnerability is made public, users should patch their systems, but attackers continue to exploit the vulnerabilities for as long as unpatched systems remain exposed on the internet.

Defending against zero-day attacks

Zero-day exploits are difficult to defend against because they are so difficult to detect. Vulnerability scanning software relies on malware signature checkers to compare suspicious code with signatures of known malware; when the malware uses a zero-day exploit that has not been previously encountered, such vulnerability scanners will fail to block the malware.

Since a zero-day vulnerability can't be known in advance, there is no way to guard against a specific exploit before it happens. However, there are some things that companies can do to reduce their level of risk exposure.

  • Use virtual local area networks to segregate some areas of the network or use dedicated physical or virtual network segments to isolate sensitive traffic flowing between servers.
  • Implement IPsec, the IP security protocol, to apply encryption and authentication to network traffic.
  • Deploy an IDS or IPS. Although signature-based IDS and IPS security products may not be able to identify the attack, they may be able to alert defenders to suspicious activity that occurs as a side effect to the attack.
  • Use network access control to prevent rogue machines from gaining access to crucial parts of the enterprise environment.
  • Lock down wireless access points and use a security scheme such as Wi-Fi Protected Access 2 for maximum protection against wireless-based attacks.
  • Keep all systems patched and up to date. Although patches will not stop a zero-day attack, keeping network resources fully patched may make it more difficult for an attack to succeed. When a zero-day patch does become available, apply it as soon as possible.
  • Perform regular vulnerability scanning against enterprise networks and lock down any vulnerabilities that are discovered.

While maintaining a high standard for information security may not prevent all zero-day exploits, it can help defeat attacks that use zero-day exploits after the vulnerabilities have been patched.

Comments

Popular posts from this blog

Understanding the Evolution: AI, ML, Deep Learning, and Gen AI

In the ever-evolving landscape of artificial intelligence (AI) and machine learning (ML), one of the most intriguing advancements is the emergence of General AI (Gen AI). To grasp its significance, it's essential to first distinguish between these interconnected but distinct technologies. AI, ML, and Deep Learning: The Building Blocks Artificial Intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. Machine Learning, a subset of AI, empowers machines to learn from data and improve over time without explicit programming. Deep Learning, a specialized subset of ML, involves neural networks with many layers (hence "deep"), capable of learning intricate patterns from vast amounts of data. Enter General AI (Gen AI): Unraveling the Next Frontier Unlike traditional AI systems that excel in specific tasks (narrow AI), General AI aims to replicate human cognitive abilities across various domains. I...

Normalization of Database

Database Normalisation is a technique of organizing the data in the database. Normalization is a systematic approach of decomposing tables to eliminate data redundancy and undesirable characteristics like Insertion, Update and Deletion Anamolies. It is a multi-step process that puts data into tabular form by removing duplicated data from the relation tables. Normalization is used for mainly two purpose, Eliminating reduntant(useless) data. Ensuring data dependencies make sense i.e data is logically stored. Problem Without Normalization Without Normalization, it becomes difficult to handle and update the database, without facing data loss. Insertion, Updation and Deletion Anamolies are very frequent if Database is not Normalized. To understand these anomalies let us take an example of  Student  table. S_id S_Name S_Address Subject_opted 401 Adam Noida Bio 402 Alex Panipat Maths 403 Stuart Jammu Maths 404 Adam Noida Physics Updation Anamoly :  To upda...

How to deal with a toxic working environment

Handling a toxic working environment can be challenging, but there are steps you can take to address the situation and improve your experience at work: Recognize the Signs : Identify the specific behaviors or situations that contribute to the toxicity in your workplace. This could include bullying, harassment, micromanagement, negativity, or lack of support from management. Maintain Boundaries : Set boundaries to protect your mental and emotional well-being. This may involve limiting interactions with toxic individuals, avoiding gossip or negative conversations, and prioritizing self-care outside of work. Seek Support : Reach out to trusted colleagues, friends, or family members for support and advice. Sharing your experiences with others can help you feel less isolated and provide perspective on the situation. Document Incidents : Keep a record of any incidents or behaviors that contribute to the toxic environment, including dates, times, and specific details. This documentation may b...