Hashes for malware are ubiquitous in our sector. And for good cause. They aid in the identification of malware samples and the standardization of information exchange among researchers, to name a couple uses.
Hash functions are a broad and intricate topic. They come in dozens, if not hundreds, with a wide range of applications, outcomes, security, and underlying calculation techniques.
We will therefore limit our discussion of hashes to cybersecurity and information security in order to save time and maintain our sanity.
What is a hash function
A hash function is an algorithm that uses any amount of bits to produce a singular output with a fixed size. The result can take the form of a hash, hash code, hash sum, hash value, checksum, digital fingerprint, or message digest. A malicious file’s hash is known as a hash lookup malware.
The hashing operation can only be performed in one direction, from a variable-length string of bits to a fixed-length output, according to mathematical guarantees.
A single change to the input results in a completely different hash sum, and the output’s uniqueness is meant to be absolute, meaning that no two distinct inputs can produce the same output.
Hash function requires
The most popular hashing algorithms are MD5, SHA-1, SHA-256, and SHA-512. Their main job in cybersecurity is to create distinctive IDs for their inputs, like malware files, so that they can be easily categorized, distributed, or (re)searched.
For more precise malware identification, grouping, comparison, and analysis, more hash methods are used.
For instance, fuzzy hashes were developed to distinguish between files that share traits or have undergone minor updates. One popular kind of fuzzy hash is SSDEEP.
Hashes: Are They Really Safe?
Whatever depends. Once thought to be uncrackable hashes are now viewed as insecure.
This may mean that the algorithm and/or the outcome can be changed, causing a collision (when the same hash value is created for two separate inputs), or being subjected to other manipulations.
The previously described MD5 hashing function is no longer thought to be secure. Depending on the intended use, several sources assert that the SHA-1, SHA-256, and SHA-512 functions are likewise insecure.
Data, including passwords, must be protected by using powerful hashing techniques. As a general rule, be sure any hash function you’re considering using complies with the security requirements of your 1) use case and 2) organization/industry).
What Do Hashes Have as a Use?
In addition to other domains, cybersecurity makes extensive use of hash algorithms. Data confidentiality and integrity, as well as authentication and non-repudiation, are where they are most frequently used. They fit the bill for the job due to the following qualities:
- They are irreversible.
- The output has a set length and is unique. 3) They significantly, even enormously, reduce the amount of original data they represent.
An example of a data structure that employs hash values to represent huge amounts of data or files is a hash table.
Quick data search is possible due to the reduction in the amount of data that must be queried and the quick cross-referencing made possible by unique identifiers.
By creating a hash and comparing it to the hash recorded for the original data, file integrity is established. The data has not been changed if the two values are identical.
Password security involves using a hashing algorithm to process user-generated passwords and storing the hash rather than the plaintext version. Passwords are protected against illegal access in this way.
Any password used for login in is hashed and compared to the previously saved hash for verification reasons.
Cybersecurity Hashes
In the cybersecurity sector, hashes are frequently used to categorize, trade, and organize malware samples. Antivirus (AV) software was one of its early uses. Antivirus software uses a database of malware hashes as a kind of blocklist.
The hashes generated for the system’s executable files are compared against the blocklist during the scanning process. A match suggests that a malicious file is there.
The list of known malware hashes is extensive and keeps expanding, which is a drawback of this detection method.
The storage and processing capacity of personal computers, intrusion detection systems (IDS/IPS), and firewalls may be soon exceeded by this volume of data. Make sure your threat intelligence is up to date and devoid of false positives or inactive indicators before using blocklists of any kind. Quality prevails over quantity!
Security software started to use heuristic/behavioral analysis to find malware as the market developed. Without this capability, polymorphic malware, for instance, might go undetected.
Beyond signature-based detection methods, malware hashes have many other uses. They standardize and facilitate the exchange of IoCs across researchers (Indicators of Compromise).
Similar to how antivirus software searches for infected PCs, threat hunters and SOC teams also employ malware hashes.
It does save a lot of time to be able to seek for a hash value rather than searching for signs of the infection. To support investigations, having high-quality malware hashes data in a TIP or SIEM is crucial.
Researchers employ hashes, such as fuzzy hashes that seek for similarities across samples, to analyze and assess malware.
Using perceptual hash data from screenshots, machine learning models can learn how to differentiate screenshots of websites with similar content, such as phishing sites.
Conclusion
Although hashes have limitations when used to detect malware at the perimeter, they are nevertheless very beneficial. Layered security is key, and you should never rely just on one tool or type of indicator to protect your network.
In the exchange of IoCs, threat analysis, and machine learning, hashes have several uses. Some of these are still fairly new yet appear to have great potential.
