Data lakes are powerful. They let organizations store massive amounts of raw data in one place, making it easier to run analytics, build models, and uncover insights. But with great power comes great risk, especially when it comes to insider threats.
Unlike external hackers who have to break in, insiders already have access. They are employees, contractors, or partners who know the systems and often have legitimate credentials. That makes them uniquely dangerous, especially when they decide to misuse their access.
Let’s break down how insiders exploit data lakes, how they get data out, and what you can do to stop them; with real world examples to show how it plays out.
How Insiders Get In
Most insider threats start with someone who already has access. It could be:
- A data engineer or admin with broad privileges
- An analyst with read access to sensitive tables
- A contractor with temporary credentials
- Or even someone whose account was compromised by an outsider
In many cases, the problem isn’t that access was stolen, it’s that access was too generous to begin with. Over time, employees accumulate permissions they don’t need anymore. Or worse, sensitive data gets copied to shared folders where anyone can grab it.
That’s exactly what happened at Desjardins, a Canadian credit union. An employee spent over two years quietly collecting customer data from a shared drive that was supposed to be temporary. In the end, nearly 9.7 million people were affected.
How They Get Data Out
Once an insider has access, the next step is exfiltration: getting the data out of the organization. Here are some of the most common methods:
1. Bulk Downloads
This is the classic move. The insider runs a big query, exports the results, and saves them locally. If no one’s watching, they might walk out with thousands or even millions of records.
At Bupa, a health insurer, an employee downloaded data on over 500,000 customers and emailed it to himself. He later tried to sell it on the dark web.
2. Personal Cloud or Email
Insiders often use personal email or cloud storage to move data. Think Dropbox, Google Drive, or even a private AWS bucket. If the company isn’t scanning outbound traffic, this can fly under the radar.
In one case, a developer tried to upload source code to an unauthorized S3 bucket. Luckily, the company had DLP tools in place and blocked the transfer.
3. API Abuse and Scripting
Tech savvy insiders might write scripts to pull data via APIs. They can automate the process, break it into chunks, and avoid detection. Some even set up scheduled jobs that look like normal ETL tasks.
Edward Snowden famously used a web crawler to scrape documents from internal NSA systems. That’s API abuse in action.
4. Exploiting Misconfigurations
Sometimes insiders find weak spots, like a storage bucket that’s accidentally public or a backup that’s not encrypted. They might change permissions to give themselves access or disable logging to cover their tracks.
In cloud environments, this can be especially risky. A single misconfigured policy can open the floodgates.
5. Covert Channels
Advanced insiders might use stealthy methods like hiding data in DNS queries or uploading it in small pieces to public forums. One Morgan Stanley employee posted client data to Pastebin, a public code sharing site.
Real-World Case Studies
Here’s a quick look at some notable insider breaches:
| Organization | Insider Profile | Exfiltration Method | Response |
| Morgan Stanley | Former employee | Posted client data on Pastebin | Fired employee, tightened encryption & monitoring |
| Tesla | Two employees | Shared 100 GB of data with media | Legal action, reinforced least privilege policies |
| Bupa | Customer service rep | Emailed 547k records to personal account | Fired employee, fined by regulator, added controls |
| Desjardins | Finance employee | Collected data from shared drive over 2 years | Overhauled security, added audits & training |
How to Protect Your Data Lake
So what can you do to stop insider threats before they cause damage? Here are the top technical controls to consider:
1. Lock Down Access
Use the principle of least privilege. Give people only the access they need and review it regularly. Segment sensitive data and use just in time access for high-risk operations.
2. Monitor Everything
Enable audit logs, track queries, and use behavior analytics to spot anomalies. If someone downloads more data than usual or accesses it at odd hours, that should raise a flag.
Set thresholds for query size, file downloads, and outbound traffic. Use DLP tools to inspect emails, uploads, and cloud syncs.
3. Encrypt and Mask Data
Encrypt data at rest and in transit. Mask sensitive fields so even if someone accesses a dataset, they can’t see personal info unless authorized.
4. Watch Departing Employees
Many insider breaches happen when someone is leaving the company. Monitor access closely during notice periods and revoke credentials promptly.
Microsoft Purview and similar tools can flag risky behavior from departing staff, like sudden spikes in downloads or access to unusual datasets.
5. Be Ready to Respond
Have a plan for incident response. Keep logs secure, automate containment (like locking accounts), and involve legal teams quickly. Learn from each incident and update your controls.
Final Thoughts
Insider threats are tricky because they don’t look like threats at first. They look like normal users doing normal things, until they aren’t.
That’s why protecting your data lake requires more than just firewalls and passwords. You need visibility, context, and smart controls that can tell when something’s off.
By learning from real incidents and putting the right safeguards in place, you can turn your data lake from a soft target into a secure asset. Because when it comes to insider threats, trust is good but verification is better.
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