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LABS
Why Is My NTP Server Costing $500/Year? Part 1

Our recent monthly Amazon AWS bills were much higher than normal—$40 [1] dollars higher than normal. What happened?

We investigated and discovered our public NTP server was heavily loaded. Over a typical 45-minute period, our instance provided time service to 248,777 unique clients (possibly more, given that a firewall may “mask” several clients), with an aggregate outbound data of 247,581,892 bytes (247 MB). Over the course of a month this traffic ballooned to 332GB outbound traffic, which cost ~$40.

This blog post discusses the techniques we used to investigate the problem. A future blog post (Part 2) will discuss how we fixed the problem.

Clue #1: The Amazon Bill

What had happened? Our account has only one instance, and it’s a t1.micro instance, Amazon’s smallest, least expensive instance. Had we deployed other instances and forgotten to shut them down? Had someone broken into our AWS account and used it to mine bitcoins? Had our instance been used in an NTP amplification attack? We scrutinized our Amazon AWS bill:

Amazon bill highlighting bandwidth charges of $40 and symmetrical in/out

This month’s Amazon AWS Bill. The bandwidth charges are surprisingly large given that the bulk of the traffic is DNS and NTP

We determined the following:

  • It’s unlikely that someone had broken into our Amazon AWS account—there was only one instance spun up during the month, and it was our t1.micro.
  • The unexpected charges were in one area only—bandwidth.
  • The bandwidth was symmetrical (i.e. the total inbound bandwidth was within 5% of the total outbound bandwidth). This would indicate that our instance was not used in a NTP amplification attack (an NTP amplification attack would be indicated by lopsided bandwidth usage: outbound bandwidth would have been much higher than inbound)

Clue #2: Amazon Usage Reports

We needed more data. We turned to Amazon’s Usage Reports.

AWS Console → My Account → Reports → AWS Usage Report → Amazon Elastic Compute Cloud

We ran a report requesting the following information:

  • Usage Types: DataTransfer-Out-Bytes
  • Operation: All Operations
  • Time Period: Custom date range
    • from: Jun 1 2013
    • to: Jun 1 2014
  • Report Granularity: Days
  • click Download report (CSV)

We downloaded the report and imported it into a spreadsheet (Apple’s Numbers). We noticed that the traffic had a thousand-fold increase on March 30, 2014: it climbed from 4.2MB outbound to 8.9GB outbound.

We graphed the spreadsheet to get a closer look at the data:

Amazon AWS Outbound Bandwidth Usage, by Day

Amazon AWS Outbound Bandwidth Usage, by Day

We used a logarithmic scale when creating the graph. A logarithmic scale has two advantages over a linear scale:

  1. it smoothes bumps
  2. it does a better job of displaying data that spans multiple orders of magnitude

We noticed the following:

  • Before 3/29/2014, daily outbound bandwidth was fairly consistent at 2-6 MB / day
  • After 3/30/2014, daily outbound bandwidth was fairly consistent at 8-12 GB / day

What happened on 3/30?

Clue #3: git log

We use git to track changes on our instance’s /etc/ directory; we use git log to see what changes happened on 3/30:

$ git log --graph --pretty=format:'%h %ci %s'
* 4346463 2014-06-11 14:38:57 +0000 apt-get update; apt-get upgrade
* 0edb10d 2014-03-29 18:41:36 +0000 ntp installed
* f8302e2 2014-03-29 17:19:31 +0000 pre-ntpd checkin
* d172264 2013-05-02 05:26:25 +0000 Initial Checkin

We had enabled NTP on 3/29.

That was also the day when we registered our server with the NTP Pool, a volunteer effort where users can make their NTP servers available to the public for time services. The project has been so successful that it’s the default “time server” for most of the major Linux distributions.

It takes about a day for the NTP Pool to satisfy itself that your newly-added server is functional and to make it available to the public—that is likely why we didn’t see any traffic until a day later, 3/30.

“Et tu, NTP?”

Could NTP be the culprit? Had our good friend NTP stabbed us in the back? It didn’t seem possible. Furthermore, the documentation on the www.pool.ntp.org website states that typical traffic is “…roughly equivalent to 10-15Kbit/sec (sic) [2] with spikes of 50-120Kbit/sec”.

But we’re seeing 740-1000kbit/sec [3]: seventy times more than what we should be seeing. And note that we’re being generous—we assume that they are referring to outbound traffic only when they suggest it should be 10-15kbit/sec; if they meant inbound and outbound combined, then our NTP traffic is one hundred forty times more than what we should be seeing.

Clue #4: tcpdump

We need to examine packets. We decide to do a packet trace on our instance for a 45-minute period:

$ sudo time -f "%e seconds" tcpdump -w /tmp/aws.pcap
tcpdump: listening on eth0, link-type EN10MB (Ethernet), capture size 65535 bytes
^C5617555 packets captured
5626229 packets received by filter
8665 packets dropped by kernel
2693.13 seconds

We don’t concern ourselves with the 8665 packets that were dropped by the kernel—they represent less than 0.15% of the overall traffic, and are thus inconsequential.

We copy the file (/tmp/aws.pcap) to our local workstation (doing traffic analysis on a t1.micro instance is painfully slow).

Is our packet trace representative? Yes.

We need to make sure our packet trace is representative of typical traffic to our server, at least in terms of throughput (kbits/sec). In other words, our packet trace should have an outbound throughput on the order of 740-1000kbit/sec.

We have a dilemma: tcpdump’s units of measurement are packets, not bytes. We will address this in two steps:

  1. We will run tcpdump to create a .pcap file that contains only the outbound packets.
  2. We will usepcap_len [4] to determine the total aggregate size of those packets in bytes.

Once we have the total number of bytes, we can determine the throughput.

$ tcpdump -r ~/Downloads/aws.pcap -w ~/Downloads/aws-outbound.pcap src host 10.206.10.174
$ ./pcap_len ~/Downloads/aws-outbound.pcap
linktype EN10MB
total len = 248453677, total packets = 2756609

We have 248453677 bytes / 2693 seconds, which works out to [5] 738 kbits / sec, which is in line with our typical outbound traffic (740-1000kbits/sec)

What percentage of our outbound traffic is NTP? 99.6%

We want to confirm that NTP is the bulk of our traffic. We want to make sure that NTP is the bad guy before we point fingers. Once again, we use tcpdump in conjunction with pcap_len to determine how many bytes of our outbound traffic is NTP:

$ tcpdump -r ~/Downloads/aws-outbound.pcap -w ~/Downloads/aws-outbound-ntp-only.pcap src port 123
$ ./pcap_len ~/Downloads/aws-outbound-ntp-only.pcap
linktype EN10MB
total len = 247581892, total packets = 2750878

We don’t care how many seconds passed; we merely care how many bytes we sent outbound (248453677) and how many of them were NTP (247581892). We determine that NTP accounts for 99.6% [6] of our outbound traffic.

NTP is the bad guy.

Clue #5: Compare against a control

We want to see if we have an excessive number of NTP clients vis-a-vis other NTP pool members. Fortunately, we have another machine (our home network’s FreeBSD firewall, also an NTP server and connected to the Comcast network) that’s also in the NTP pool. We’ll pull statistics from there:

$ sudo time tcpdump -i em3 -w /tmp/home.pcap port 123
tcpdump: listening on em3, link-type EN10MB (Ethernet), capture size 65535 bytes
^C381383 packets captured
468696 packets received by filter
0 packets dropped by kernel
     2209.59 real         0.25 user         0.19 sys

We are only concerned with outbound NTP traffic. tcpdump and pcap_len to the rescue:

$ tcpdump -r ~/Downloads/home.pcap -w ~/Downloads/home-outbound-ntp-only.pcap src port 123 src host 24.23.190.188
$ pcap_len ~/Downloads/home-outbound-ntp-only.pcap
linktype EN10MB
total len = 17161678, total packets = 190685

Let’s determine our home NTP outbound traffic: 17161678 bytes / 2209 secs = 7769 bytes / sec = 62 kbits /sec.

Let’s determine our AWS NTP outbound traffic: 247581892 bytes / 2693 secs = 91935 bytes / sec = 735 kbits /sec

Our AWS server is dishing out 11.8 times the NTP traffic that our home server is. But that’s not quite the metric we want; the metric we want is “how much bandwidth per unique client (unique IP address)

We determine the number of unique NTP clients that each host (AWS and home) have:

tcpdump -nr ~/Downloads/aws-outbound-ntp-only.pcap  | awk ' { print $5 } ' | sed 's=.[0-9]*:==' | sort | uniq | wc -l
  248777
tcpdump -nr ~/Downloads/home-outbound-ntp-only.pcap | awk ' { print $5 } ' | sed 's=.[0-9]*:==' | sort | uniq | wc -l
   34908

Our AWS server is handling 7.1 times the number of unique NTP clients that our home server is handling. This is troubling. It means that certain AWS NTP clients are using up more bandwidth than they should. Furthermore, we need to remember that we ran tcpdump longer (2693.13 seconds) on our AWS server than we did (2209.59 seconds) on our home server, giving AWS more time to collect unique clients. In other words, the ratio is probably worse (if we extrapolate based on number of seconds, the AWS server is spending twice the bandwidth for each client than the home server).

Clue #6: Greedy (broken?) clients

We suspect that broken/poorly configured clients may account for much of the traffic. The grand prize belongs to an IP address located in Puerto Rico (162.220.96.14) managed to query our AWS server 18,287 times over the course of 2693 seconds, which works out to 6.7 queries / second.

The runner-up was also located in Puerto Rico (70.45.91.171), with 12,996 queries at a rate of 4.8 queries / second. Which begs the question: what the heck is going on in Puerto Rico?

Let’s take a brief moment to discuss how we generated these numbers: we lashed together a series of pipes to list each unique IP address and the number of packets our instance sent to that address, converted the output into CSV (comma-separated values), and then imported the data into a spreadsheet for visual examination.

tcpdump -nr ~/Downloads/aws-outbound-ntp-only.pcap | awk ' { print $5 } ' | sed 's=.[0-9]*:==' | sort | uniq -c | sort -n > /tmp/ntp_clients.txt
awk '{print $1}' < /tmp/ntp_clients.txt | uniq -c | sed 's=^ *==; s= =,=' > /tmp/clients.csv

And let’s discuss the graph below. It shows the correlation between the number of unique clients, and the number of queries each one makes. We want to see, for example, if we block any client that makes more than 289 queries in a 45-minute period, how much money would we save? (In this example, we would save $48 over the course of the year)

Cumulative NTP Outbound by Unique IP

This chart is tricky: let’s use an example. The 25% on the Y-axis crosses 23 on the X-axis, which means, “25% of the NTP traffic is to machines which have made 23 or fewer queries”

Now we have some tools to make decisions. As with most engineering decisions, economics has a powerful say:

If we block IP addresses
that query time more than
(over the course
of 45 minutes)…
…then we cut
our bandwidth…
…and spend
this much
annually
0 100% $0
3 90% $48
23 75% $120
51 50% $240
79 25% $360
289 10% $432
864 5% $456
18287 0% $480

But we are uncomfortable with this heavy-handed approach of blocking IPs based on nothing more than the number of queries. Our assumption that a large number of queries is indicative of a faulty NTP client is misguided: For example, a corporate firewall would appear as a faulty client, but merely because it’s passing along hundreds of queries from many internal workstations.

We’ll explore finer-grained approaches to determining faulty clients in the next blog post. Stay tuned.


Footnotes

1 The yearly cost is slightly less than $500, closer to $480; however, we decided to exercise poetic license for a catchy headline. Yes, in the finest tabloid tradition, we sacrificed accuracy on the altar of publicity.

2 The SI prefix “k” (kilo) should be lowercase. Just sayin’.

3 Math is as follows:

8,000,000,000 bytes / day

× 1 day / 24 hours

× 1 hour / 3600 seconds

× 8 bits / 1 byte

× 1 kbit / 1000 bits

= 740.740740740741 kbit / sec

4 pcap_len is a program of dubious provenance that was uploaded to a tcpdump mailing list in 2004. Thanks Alex Medvedev wherever you are.

But we are not country bumpkins who trust anyone who happens to post code to a mailing list. We want to confirm that the pcap_len program works correctly. We need to know two things:

  1. What is the size of an NTP packet?
  2. What is the overhead of the pcap file format?

The size of the NTP packet is straightforward, 90 bytes:

And the pcap file format overhead per packet? 16 bytes.

  • Size of the AWS outbound NTP pcap file: 291595964
  • Size of the AWS outbound NTP packets according to pcap_len: 247581892
  • Ratio of NTP packet + pcap overhead to NTP packet: (90 + 16)/90 = 1.17777

247581892 * 1.17777 = 291596450
(within 486 bytes of 291595964, which is good enough for us).

Yes, pcap_len passes our cross-check.

5 Math is as follows:

248453677 bytes / 2693 seconds

= 92259 bytes / sec

× 8 bits / 1 byte

× 1 kbit / 1000 bits

= 738 kbits /sec

6 Math is as follows:

( 247581892 / 248453677 ) × 100 = 99.6%

Comments
  1. Augustine says:

    I wonder if Puerto Rico has run out of its pool of IPv4 addresses. After Europe and Asia, just this month Latin America as well, have exhausted their IPv4 pools, many local ISPs have resorted to using NAT to deal with the scarcity of addresses (of course, after years procrastinating IPv6 and pretending that this day wouldn’t come about). Given that the source is a Puerto Rican ISP, and one of the offending addresses from a small /21 network, it’s possible that NAT is to blame. As ISP NAT increasingly becomes more prevalent, this is going to be rather touchy to deal with abuses. For is it an abuser or just several innocent users behind a NAT?

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