Cybersecurity experts can all agree on one thing. Dark-web activity can be studied in order to detect all types of patterns. Such patterns can then be studied to expose all types of attacks and risks. It does not matter if an attack is pending or already in progress, they can usually be exposed.
The Need for Dark-Net Scraping
Cybersecurity risks can appear instantly like a flash without many victims expecting it. Cyber-criminals are racing to profit from stolen data following successful data breaches. It is not uncommon for such data to get published almost instantaneously after such attacks. In some extreme cases, it can take minutes.
It critical that people find out on time if their data has been breached. Cyber-safety pundits claim that the average time taken for a victim to find out his data was breached is 197 days. IBM published a report on this situation in 2018. The report titled "Cost of a Data Breach" reveals a lot of relevant details on the situation. It was pointed out in the paper that over $1 million in losses can be avoided if that number is lowered to 30 days.
Once again, this shows how technology is evolving. Companies require new tactics to ensure the safety of their customers data. It is now a rule of thumb for organizations to employ dark-web monitoring techniques. Dark-web filtering systems that can look for customer data will reveal possible attacks. It is not uncommon for companies to suffer a breach without them knowing for months.
A large number of cybersecurity risk factors must be reviewed for this method of finding attacks. A context rich intelligence framework is required to protect organizations and its data.
The Largest Risks
Phishing and whaling campaigns have evolved. They are becoming highly destructive to victims. Dark-net threat intelligence can access tons of information on the dark-net and filter it looking for stolen data. Although not completely defending the company, such software can save a lot of money. Such scanning tool with equip stakeholders with much needed information. Such information can be used to make the stolen data unusable.
Credential Exchange and Personal Identifiable Data
Every time a data breach occurs, many methods can be used to identify it. One specific method is commonly used to indicate the aftermath of such attacks. Personal identifiable data can be used to find records stolen from an organization. Data can be bought on the dark-web for as low as $20. Most of that data is sourced though large targeted attacks.
Personal identifiable data consists of different types of information. That includes usernames, emails, password and often banking information. A lot of other sensitive data can be included depending on the organization targeted. Most of this data is distributed through out dark-net markets. Such listings can offer companies a clue as to what happened in order to avoid financial losses.
Threat intelligence firm 4iQ made a very interesting discovery. A huge database was found floating around the dark-net. The database consisted of stolen user data and contains over 1.5 billion records. This finding shows that companies need to establish proper filters. Such filters are required in order to confirm the relevance of the data. Not having the proper systems set up might result in false warnings.
Company and Organization Discussions
Other methods are used by organizations in order to detect potential risks. One risk factor identifies is the mention of a company's name on the dark-web. Forum posts, paste platforms and chatroom's are all being scraped for such information.
Organizations consistently use this tactic to detect possible threats. This method extends way beyond the aftermath of such attacks. It is not uncommon for upcoming attacks to be flagged before they even happen. Many cyber-criminals use dark-net forums and chatroom's to prepare for the attacks. Such inside information can give a company enough time to prepare for the attack.
Trade Secret Discussions
Threat actors love to exploit as much as possible for their own good. Trade secrets and competitive intelligence is another area commonly exploited by such criminals. Many cyber-criminals use stolen data to gain insider information for massive economic gains.
One specific example can be drawn from 2018. An incident involving Russian cyber-criminal attack. The attackers ended up selling access to a law firm's network and other assets for $3,500. Such information could then be purchased by competing law firms and be used to win cases.
If the attack on the law firm was detected ahead of time or much sooner, a lot would have been saved. Not only the waste countless time and money would have been avoided, but the brand image would have remained intact.
The dark-net has evolved to host countless stolen user data. Just like every cyber-crime, thanks to the dark-net, the sale of stolen data has been popularized. Threat actors used to breach companies and use the data gathered for their own profits. Now instead of using the actual data, criminals can profit just from selling it. This industry is costing organizations millions every year. This is where the need to adapt came from. Systems that scan for such stolen data can save both the victim and the organization a lot of money.