6.033 | Spring 2018 | Undergraduate

Computer System Engineering

Week 13: Security Part III

Lecture 23 Outline

Disclaimer: This is part of the security section in 6.033. Only use the information you learn in this portion of the class to secure your own systems, not to attack others.
  1. Today’s Threat Model
    • Last time: adversary tried to observe or tamper with packets.
    • Today: adversary is not just passively observing the network, but actively using it to attack users (more actively than the replay/reflection/man-in-the-middle attacks we saw last time).
    • Some attacks today don’t require adversary to observe packet contents; secure channels won’t help.
  2. DDoS Attacks
    • Adversary’s goal: bring down a service (e.g., take down the root DNS servers).
    • Strategy: congest the service. Make it spend time handling the adversary’s requests so that it can’t get to legitimate ones.
    • DoS (“denial of service”) attack:
      • Adversary sends a bunch of traffic to the service (in many cases even invalid requests will work), queues fill up, packets dropped, etc.
    • DDoS (“distributed DoS”) attack:
      • Mount the attack from multiple machines.
    • Can target any resource: bandwidth, routing systems, access to a database, etc.
    • Consequences of (D)DoS attacks:
      • A server being down for a few hours might not seem like the end of the world. But…
      • Could be bank transactions.
      • Could be DNS root servers (would bring Internet to a stand-still).
      • Could be on high-frequency trading machines, affect the stock market, etc.
  3. Botnets
    • Can’t we just toughen up our defenses? Add more bandwidth? How much traffic can one adversary generate?
    • Botnets: large (~100,000 machines) collection of compromised machines controlled by an attacker.
      • Make it very easy to mount DDoS attacks.
      • Can be rented surprisingly cheaply.
        • PLEASE DO NOT DO THIS.
    • How botnets work in five minutes:
      • How do machines get compromised (and become part of the botnet)?
        • Lots of ways. Common way: user visits vulnerable website. Vulnerability is usually a cross-site scripting attack.
          Example:
          • TrustedBlog.com has a box for users to enter comments on blogs.
          • Attacker embeds an executable script in his comment.
          • When users browse, server sends comments to their browsers which execute the script, which sends the user’s cookie to the attacker’s site.
        • XSS script to compromise a botnet machine causes user to download a “rootkit”, which compromises the machine.
          • See tomorrow’s recitation.
        • Bots contact command and control (C&C) servers which give them commands.
      • How to combat botnets:
        • Block IP addresses? Ineffective. Bots can change IP addresses rapidly.
        • Distribute systems so that DDoS attacks don’t have a centralized component to bring down? Not bad, but as we’ve seen, distribution => complexity.
  4. Network Intrusion Detection Systems (NIDS)
    • If we wanted to block IP addresses, how would we even figure out which IPs were part of the botnet?
    • Broader question: how do we detect network attacks?
    • Two approaches:
      • Signature-based: Keep a database of known attack signatures and match traffic against the database.
        • Pros: Easy to understand the outcome and ccurate in detecting known attacks.
        • Cons: Can’t discover new attacks and can only get the signature after the attack has already happened at least once.
      • Anomaly-based: Match traffic against a model of normal traffic and flags abnormalities.
        • Pros: Can deal with new attacks.
        • Cons: How do we model normal traffic? Less accurate detection of known attacks.
    • Many systems take a hybrid approach.
      • Most also give users the ability to, once an attack is (passively) detected, do something to (actively) prevent it.
    • Example intrusion-detection systems:
  5. How to Evade NIDS
    • Suppose we build a NIDS to scan traffic for a particular string (“root”). Seems easy.
    • Difficult because attacker can force confusing state on the NIDS (see slides).
    • Another way to evade NIDS: mount an attack on the detection mechanism.
  6. Attacks that Mimic Legitimate Traffic (and thus are even harder to detect)
    • HTTP flooding:
      • Attacker floods webserver with completely legitimate HTTP requests to download a large file or perform some computationally intensive database operation.
    • TCP SYN floods:
      • TCP connections start with a “handshake”, which cause the server to keep some state about the connection until the client completes the handshake.
      • Attacker can initiate many handshakes, exhaust state on the server.
    • Optimistic ACKs:
      • Attacker starts TCP communication with victim, ACKs packets that it hasn’t received yet.
      • Victim sends more and more traffic to the attacker, saturating their own link.
    • DNS reflection/amplification:
      • Bots locate DNS nameservers (even better if they are DNSSEC-enable).
      • Bots send DNS requests to these nameservers.
        • Spoof sources to be the victim’s IP address.
        • If DNSSEC-enable, request the relevant info. DNSSEC responses tend to be very large.
      • Result: Large DNS responses that go to the victim’s machine.
  7. Attacks on Routers
  8. Moral of the Story
    • Secure channels are great, but adversaries can still use the network to mount attacks.
    • These attacks become devastating if they attack parts of the Internet’s infrastructure (e.g., DNS, BGP).
    • Proposals exist to secure the infrastructure (DNSSEC, Secure BGP), but there are problems.
    • It should blow your mind—and worry you—that so much of the Internet is unsecured.

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Spring 2018
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